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Introductory Notes

* Income is “a flow of purchasing power” that comes from work, investments, and other sources, like government benefits.[1] [2]

* Per the Organization for Economic Cooperation and Development:

Income allows people to satisfy their needs and pursue many other goals that they deem important to their lives, while wealth makes it possible to sustain these choices over time. Both income and wealth enhance individuals’ freedom to choose the lives that they want to live.[3]

* Some common measures of income in the U.S. are reported by the Congressional Budget Office, Census Bureau, Bureau of Labor Statistics, Bureau of Economic Analysis, Internal Revenue Service, and Federal Reserve.[4] [5] [6] [7] [8] [9]

* Accurate comparisons of income require careful use of economic data.[10] [11] Definitions of income vary by source, and the Census Bureau has 17 different measures of income.[12] [13] [14] [15] Such measures have contrasting strengths and weaknesses, such as these:

  • The Congressional Budget Office publishes a comprehensive measure of household income, but it takes significant time to prepare. Thus, the data published in 2016 reports income for 2013.[16]
  • Census Bureau income data typically does not include “noncash benefits, such as food stamps, health benefits, and subsidized housing.”[17]
  • According to the Census Bureau, its income estimates consistently “fall short of the benchmarks—across surveys, across time, and across income categories” when compared with independent sources.[18] [19] [20]
  • IRS data provides detailed information on top incomes, but it does not measure household income and excludes non-taxable income and people who don’t file tax returns.[21] [22]

* Various government agencies use different indexes to adjust for inflation.[23] [24] [25]

* Differing methods of income measurement can lead to materially different conclusions about economic conditions.[26] [27]

* Besides income and wealth, other key measures of financial wellbeing include consumption and changes in wealth over time.[28]

* Government agencies often group people into brackets according to their income, with the middle group considered as the “middle class.” Median income—“the amount which divides the income distribution into two equal groups, one having incomes above the median, and the other having incomes below the median”—is another common way to define the middle class.[29] [30] [31]

* Comparisons of income groups over time often do not represent the experiences of specific people. This is because people typically move through life stages in which their income varies significantly, causing them to move in and out of different income groups.[32] [33]

* Unless otherwise stated, all international comparisons of income in this research are provided in “purchasing power parities” or PPPs. Purchasing power parities allow for accurate measures of economic data across countries, because they relate the prices of the same goods and services in different nations.[34] [35]

* In keeping with Just Facts’ Standards of Credibility, all graphs in this research show the full range of available data, and all facts are cited based upon availability and relevance, not to slant results by singling out specific years that are different from others.

Income

* In 2013, U.S. households had an average income of $100,200. This figure includes both market and government income, and it varied by income group as follows:

Household Incomes by Income Group

[36] [37]

* From 1979 to 2013, the inflation-adjusted average income of U.S. households increased by $35,400 or 55%. This varied by income group as follows:

Inflation-Adjusted Household Income

Income Group

1979

2013

Increase From 1979–2013

Dollars

Percent

Lowest 20%

$18,200

$25,400

$7,200

40%

Second 20%

$37,100

$47,400

$10,300

28%

Middle 20%

$55,500

$69,700

$14,200

26%

Fourth 20%

$75,100

$103,700

$28,600

38%

Highest 20%

$142,400

$265,000

$122,600

86%

Top 1%

$547,900

$1,571,600

$1,023,700

187%

All Groups

$64,800

$100,200

$35,400

55%

[38] [39]


* In 2013, U.S. households had a median income of $79,200, which was reduced to about $69,200 after paying federal taxes.[40] [41]

* From 1979 to 2013, inflation-adjusted median household income increased by $17,800 or 29%. After federal taxes, median household income increased by about $19,700 or 40%:[42] [43]

Inflation-Adjusted Median Household Income

[44] [45]

Sources of Income

Overview & Trends

* The two broad categories of income are:

  1. market income, which includes cash and non-cash income from sources such as wages, employer-paid health insurance benefits, business income, capital gains, and pension plans.[46]
  2. government benefits, which include cash and non-cash income from the government, such as Social Security, welfare benefits, food stamps, and Medicare benefits.[47]

* In 2013, U.S. households obtained 86% of their income from the market and 14% from government. This varied by income group on average as follows:

Income Source by Income Group

[48] [49]

* Between 1979 and 2013, government benefits rose from 9% of total household income to 14%, which is a 58% increase. This varied by income group as follows:

Average Portion of Household Income From Government Benefits

Income Group

1979

2013

Change

Percentage Points

Percent

Lowest 20%

48%

38%

-11

-22%

Second 20%

19%

34%

15

76%

Middle 20%

8%

24%

15

183%

Fourth 20%

5%

14%

10

194%

Highest 20%

2%

5%

2

84%

All Groups

9%

14%

5

58%

[50] [51]

* In 1979, roughly 40% of U.S. households received more in federal, state, and local government benefits than they paid in federal taxes:

Government Benefits v. Federal Taxes 1979

[52] [53]

* In 2013, roughly 60% of U.S. households received more in federal, state, and local government benefits than they paid in federal taxes:

Government Benefits Federal v. Federal Taxes 2013

[54] [55]

* Government benefits can suppress market income by:

  • providing the means and incentive not to work.[56] [57]
  • reducing the incentive to work by cutting take-home pay (if taxes are raised to pay for the benefits).[58] [59] [60]
  • depressing wages by decreasing productivity-enhancing investments (if governments borrow the money to pay for the benefits).[61] [62]

Market Income Breakdown

* In 2013, cash wages and salaries accounted for 61% of market income for U.S. households. Capital and business income provided 28%, and employer-paid benefits made up the remaining 11%. This varied by income group on average as follows:

Sources of Household Market Income

[63] [64]

* In 1979, benefits paid by employers accounted for 10% of employee compensation. By 2013, this figure had risen to 15%.[65] [66]


Government Income Breakdown

* The two largest sources of household government income are Social Security and Medicare, both of which benefit elderly and disabled people.[67] [68] [69]

* In June of 2016, 60.5 million people—19% of the U.S. population—received Social Security benefits.[70]

* In 2017, roughly 58 million people—18% of the U.S. population—received Medicare benefits.[71]

* In 2012, about 52 million people—21% of the U.S. population—received benefits from one or more of these six means-tested federal welfare programs:

  1. Medicaid
  2. Supplemental Nutrition Assistance Program (Food Stamps)
  3. Supplemental Security Income
  4. Housing Assistance
  5. Temporary Assistance for Needy Families (Cash Welfare)
  6. General Assistance[72]

* In 2004, 17% of the U.S. population received benefits from one or more of the above means-tested federal welfare programs.[73]

* In 2013:

  • Social Security provided 44% of government benefits to U.S. households.
  • Medicare provided 27%.
  • Medicaid provided 15%.
  • Non-Social Security cash programs provided 10%.
  • Other non-cash programs provided 4%.
  • These figures varied by income group on average as follows:
Sources of Household Government Benefits

[74] [75]

Gross Domestic Product

Overview & Trends

* Gross domestic product (GDP) measures national economic output, or the value of all goods and services that a country produces in a year. GDP is defined by the equation: Hours worked × Labor productivity.[76] [77]

* Per capita GDP—or GDP divided by the population—is often used to measure a country’s standard of living. Per the textbook Macroeconomics for Today:

GDP per capita provides a general index of a country’s standard of living. Countries with low GDP per capita and slow growth in GDP per capita are less able to satisfy basic needs for food, shelter, clothing, education, and health.[78]

* In the U.S. from 1947 to 2016, the average inflation-adjusted GDP per person rose by 283% :[79]

U.S. Inflation-Adjusted GDP Per Capita

[80]

* In the U.S. from 2010 to 2015, inflation-adjusted GDP growth beyond population growth was 39% below the average of the 25 years (1982–2006) prior to the Great Recession (2007–2009):[81]

Inflation-Adjusted GDP Growth Beyond Population Growth, 5-Year Moving Average

[82]


Effects of Government Debt

* In 2012, the Journal of Economic Perspectives published a paper about the economic consequences of government debt. Using 2,000+ data points on national debt and economic growth in 20 advanced economies (such as the United States, France, and Japan) from 1800–2009, the authors found that countries with national debts above 90% of GDP averaged 34% less real annual economic growth than when their debts were below 90% of GDP.[83]

* As of November 1, 2017, the debt/GDP level in the U.S. was 105%.[84]

* In 2013, the Political Economy Research Institute at the University of Massachusetts, Amherst, published a working paper about the economic consequences of government debt. Using data on national debt and economic growth in 20 advanced economies from 1946–2009, the authors found that countries with national debts over 90% of GDP averaged:

  • 31% less real annual economic growth than countries with debts from 60% to 90% of GDP,
  • 29% less real annual economic growth than countries with debts from 30% to 60% of GDP,
  • and 48% less real annual economic growth than countries with debts from 0% to 30% of GDP.[85]

* The authors of the above-cited papers have engaged in a heated dispute about the results of their respective papers and the effects of government debt on economic growth. Facts about these issues can be found in Just Facts’ article, “Do Large National Debts Harm Economies?

Consumption

Overview & Trends

* Personal consumption is a comprehensive measure of the goods and services consumed by households. It includes goods and services:

  • directly purchased by households.
  • given to households by non-profit organizations.
  • “financed by third-party payers on behalf of households, such as employer-paid health insurance and medical care financed through government programs.”[86] [87]

* Per the World Bank:

Consumption is conventionally viewed as the preferred welfare indicator, for practical reasons of reliability and because consumption is thought to better capture long-run welfare levels than current income.[88] [89] [90]

* In the United States between 1929 and 2016, the average inflation-adjusted consumption per person rose by 5.6 times:

Inflation-Adjusted Consumption Per Person

[91]

* The U.S. Department of Labor collects data on a subset of consumption called “consumer expenditures.” This includes all direct purchases by households, including those made with the proceeds of government benefits like cash welfare and food stamps. It does not include goods and services received via Medicaid, Medicare, or employer-provided health insurance, except for co-pays and out-of-pocket expenses.[92] [93] [94] [95]

* The average consumer spending of middle-income U.S. households is almost equal to their reported, before-tax, cash income.[96] The ratios of spending to income for other groups vary as follows:

Income & Consumption Levels, and Rate of Consumption to Income

[97]

* Low-income households typically have much higher consumption than income, mainly due to unreported income.[98] [99] [100] Per the Journal of Human Resources, “substantial evidence” indicates that consumption data:

  • is more accurately “measured than income for those with few resources.”
  • “performs better as an indicator of low material well-being.”
  • provides policymakers with better information to decide “on appropriate benefit amounts for programs such as Food Stamps.”[101]

* The Department of Labor explains that consumers can temporarily spend more than their income by borrowing or “drawing down savings and investments.”[102] Thus, some people in the lowest income group “have expenditures that are more typical of upper-income consumers.”[103]

* Between 1989 and 2015, the average inflation-adjusted consumer expenditures of the bottom 20% of households increased by $4,326. This gain closed the 1989 gap between the bottom 20% and the next income group by 47%. The gap closures between the other groups varied as follows:

Inflation-Adjusted Expenditures

Income Group

Year

Portion of 1989 Gap Closed

1989

2015

Bottom 20 Percent

$20,296

$24,622

47%

Second 20 Percent

$29,561

$35,529

51%

Middle 20 Percent

$41,223

$46,363

31%

Fourth 20 Percent

$57,612

$64,381

21%

Top 20 Percent

$89,443

$111,633

[104] [105]


Patterns & Priorities

* Per the Bureau of Labor Statistics “consumption patterns indicate the priorities that families place on the satisfaction of the following needs”:

  • food
  • clothing
  • shelter
  • utilities
  • health
  • transportation
  • education[106]

* In 2015, shelter accounted for 20% of median-income household expenditures. The figures for other goods and services varied as follows:

Median Income Household Expenditures

[107] [108]

* In 1901, U.S. households spent 43% of their income on food. By 2015, spending on food had decreased to 13% of income. The spending levels for other expenses varied as follows:

Average Annual U.S. Expenditure Shares

[109] [110] [111]

* Per the U.S. Bureau of Labor Statistics:

Perhaps as revealing as the shift in consumer expenditure shares over the past 100 years is the wide variety of consumer items that had not been invented during the early decades of the 20th century but are commonplace today. In the 21st century, households throughout the country have purchased computers, televisions, iPods, DVD players, vacation homes, boats, planes, and recreational vehicles. They have sent their children to summer camps; contributed to retirement and pension funds; attended theatrical and musical performances and sporting events; joined health, country, and yacht clubs; and taken domestic and foreign vacation excursions. These items, which were unknown and undreamt of a century ago, are tangible proof that U.S. households today enjoy a higher standard of living.[112]

* In 2015, 87% of U.S. homes had air conditioning. The average usage or possession rates for air conditioning and other appliances varied by income group as follows:

Average Usage or Possession Rates by Income Group

Income Group

Appliance

Air Conditioning

Dishwasher

Clothes Washer

Clothes Dryer

Less than $20,000

81%

37%

63%

57%

$20,000 to $40,000

85%

59%

79%

77%

$40,000 to $60,000

90%

70%

89%

87%

$60,000 to $80,000

88%

77%

88%

87%

$80,000 to $100,000

91%

87%

93%

93%

$100,000 to $120,000

91%

89%

95%

94%

$120,000 to $140,000

91%

91%

93%

93%

$140,000 or More

93%

92%

91%

91%

All Homes

87%

68%

83%

81%

[113]

* As of 2015, 86% of U.S. homes had internet access. The average usage and possession rates for different types of electronic devices and services varied by income as follows:

Average Usage or Possession Rates by Income Group

Income Group

Electronic Device or Service

Primary TV 40” or Larger

Cable & Digital Video Recorder

Internet Access

Desktop Computer

Laptop Computer

Smartphone

Less than $20,000

33%

26%

64%

25%

39%

54%

$20,000 to $40,000

44%

38%

80%

38%

53%

67%

$40,000 to $60,000

53%

49%

90%

42%

66%

80%

$60,000 to $80,000

51%

49%

94%

44%

74%

83%

$80,000 to $100,000

65%

60%

97%

48%

77%

89%

$100,000 to $120,000

60%

57%

96%

53%

81%

91%

$120,000 to $1400,000

56%

63%

100%

56%

83%

94%

$140,000 or More

62%

65%

99%

58%

90%

95%

All Homes

49%

51%

86%

42%

64%

76%

[114]


Perceptions

* In 2015, U.S. residents of varying income, race, education, and marital status described their overall economic well-being as follows:

Self-Perception of Overall Economic Well-Being

Characteristic

Finding It Difficult to Get By

Just Getting By

Doing Okay

Living Comfortably

Family Income

Less than $40,000

18%

32%

39%

12%

$40,000–$100,000

4%

19%

47%

29%

Greater than $100,000

2%

8%

37%

54%

Race/Ethnicity

White, non-Hispanic

9%

20%

41%

30%

Black, non-Hispanic

10%

28%

41%

20%

Hispanic

12%

25%

43%

21%

Education

High school degree or less

13%

26%

41%

20%

Some college or associate degree

9%

25%

42%

24%

Bachelor’s degree or more

6%

14%

40%

41%

Marital and Parental Status

Unmarried, no children under 18

12%

25%

42%

21%

Married, no children under 18

6%

15%

43%

37%

Unmarried, children under 18

19%

34%

34%

13%

Married, children under 18

7%

22%

40%

31%

Overall

9%

22%

41%

28%

[115]

International Comparisons

Gross Domestic Product

* Gross domestic product (GDP) measures national economic output, or the value of all goods and services that a country produces in a year.[116] [117]

* Per the U.S. Bureau of Labor Statistics:

GDP per capita [person], when converted to U.S. dollars using purchasing power parities, is the most widely used income measure for international comparisons of living standards.[118]

* Per the textbook Macroeconomics for Today:

Countries with low GDP per capita and slow growth in GDP per capita are less able to satisfy basic needs for food, shelter, clothing, education, and health.

* In 2016, the worldwide average GDP per person was $15,066. This varied from a high of $52,307 in North America to a low of $3,453 in Sub-Saharan Africa:

GDP Per Person in Major Regions of the World

[119]

* In 2015, the U.S. ranked 5th among 35 developed nations in average GDP per person. Other developed nations ranked as follows:

GDP Per Person in Developed Nations

[120]


Disposable Income

* Per the Organization for Economic Cooperation and Development:

Disposable income, as a concept, is closer to the idea of income as generally understood in economics, than is either national income or gross domestic product (GDP).[121] [122]

* Household gross adjusted disposable income equals:

  • all income received from work, investments, governments, gifts, and charities (including non-cash income like healthcare benefits, housing, and food).
  • minus all taxes paid and all money willingly given away.[123] [124] [125]

* In 2015, the United States ranked first among 32 developed nations in gross adjusted disposable income per household:

Gross Adjusted Disposable Income per Household

[126]


Low-Income Wages

* Real wages are a measure of how much workers can buy with the money they earn from one hour of work.[127]

* In 2012, Princeton University economist Orley Ashenfelter authored a working paper that compared the real wages of McDonald’s workers in over 60 countries. He did this by comparing how many Big Macs they could buy with their income from an hour of work. The advantage of using this measure is that:

  • “the workers are thus using identical skills, using identical technology, and producing the same product.”
  • “it does not rely on exchange rates at all. It is a direct physical measure of the output a worker may purchase with an hour of work, and it is comparable over time and across space.[128]

* This study found that McDonald’s workers in the United States had the second-highest real wages of McDonald’s workers in all economic regions:

Number of Big Macs a McDonald’s Worker Could Buy with One Hour of Wages

[129]

Productivity

Overview & Trends

* Labor productivity is the amount of goods and services that workers produce in an hour.[130] [131] [132] [133]

* Per Federal Reserve Chair Janet Yellen (and various other economists with wide-ranging political views):

The most important factor determining living standards is productivity growth, defined as increases in how much can be produced in an hour of work. Over time, sustained increases in productivity are necessary to support rising incomes.[134] [135] [136] [137] [138] [139] [140]

* Per the Congressional Budget Office, “a small change in the growth of productivity” over an extended period can do more harm than recessions, because low labor productivity reduces economic “output by an ever-increasing amount.”[141]

* As an example of labor productivity growth, U.S. businesses increased their inflation-adjusted output by 42% from 1998 to 2013 without any increase in work hours.[142]

* Labor productivity growth is driven by three primary factors:

  • investment in capital resources, like machinery, buildings, and computers.
  • workers becoming more skilled.
  • technological innovation.[143] [144] [145]

* Because productivity growth often fluctuates over the short term, it is sometimes measured in five year moving averages.[146] [147]

* The U.S. Bureau of Labor Statistics considers the nonfarm business sector to be the best single indicator of labor productivity for the U.S. economy. This is because it excludes sectors that are volatile or don’t produce concretely measurable output.[148] [149] [150]

* From 2011 to 2015, nonfarm labor productivity growth was 72% below the average of the prior six decades:

U.S. Nonfarm Business Labor Productivity Growth 5-Year Rolling Average

[151]

* If the labor productivity slowdown that took place from 2005–2015 had not occurred, the U.S. economy in 2015 would have been about $3 trillion larger. This amounts to an average of $23,400 for every household in the United States.[152]

* Productivity growth can be suppressed by a variety of factors, such as:

  • education that does not equip people with practical skills.[153] [154]
  • government debt that diverts money away from capital investments.[155]
  • immigration of low-skilled workers [156] [157]
  • immigration of people who don’t learn to speak English proficiently.[158]
  • laws and regulations that prohibit workers from using efficient or cost-effective means of production.[159] [160] [161] [162]

Worker Compensation

* Some politicians, commentators, and policy analysts have claimed that worker productivity has risen more than worker compensation for decades, such as:

  • Lawrence Mishel, president of the Economic Policy Institute: “[T]he pay of a typical worker has not grown along with productivity in recent decades, even though it did just that in the early post-war period.”[163]
  • Sen. Elizabeth Warren: “Productivity and GDP just kept going up, but workers were left behind.”[164]
  • The New York Times editorial board: “But for the vast majority of workers, pay increases have lagged behind productivity in recent decades.”[165]
  • Hillary Clinton: “You’re working harder but your wages aren’t going up.”[166]
  • The Atlantic: “[B]etween worker wages and worker productivity, there’s a significant and, many believe, problematic, gap that has arisen in the past several decades.”[167]
  • Paul Krugman, Nobel Prize-winning economist and Princeton University professor: “The divergence between pay and productivity—a lot of productivity gains, almost total failure to trickle down—is one of the most striking features of American economics these past 40 (!) years.”[168]

* Per Ph.D. economist Martin Feldstein, professor of economics at Harvard University and President Emeritus of the National Bureau of Economic Research:[169]

  • “Two principal measurement mistakes have led some analysts to conclude that the rise in labor income has not kept up with the growth in productivity.”
  • “The first of these is a focus on wages rather than total compensation. Because of the rise in fringe benefits and other noncash payments, wages have not risen as rapidly as total compensation. It is important therefore to compare the productivity rise with the increase of total compensation rather than with the increase of the narrower measure of just wages and salaries.”
  • “The second measurement problem” is that some studies use differing inflation adjustments for compensation and productivity, and “it is misleading in this context to use two different deflators, one for measuring productivity and the other for measuring real compensation.”
  • Between 1970 and 2006, employee compensation per hour “increased at approximately the same annual rate” as productivity when all compensation is included and is “adjusted for inflation in the same way.”[170]

* Another reason behind claims that worker compensation has not kept pace with

productivity growth is that some studies compare the compensation of one group of workers to the productivity of another group of workers.[171] [172]

* An objective comparison of labor productivity and compensation requires that:

  • all compensation is included.[173]
  • the data be adjusted for inflation using the same price index.[174] [175] [176]
  • the productivity and compensation of the same workers are examined.[177]

* The U.S. government typically adjusts:

  • productivity data for inflation using an “implicit price deflator.”[178] [179] [180]
  • worker compensation data for inflation using the Consumer Price Index.[181] [182] [183]

* When adjusted for inflation using:

  • differing price indexes, average labor productivity and hourly compensation increased at the same rate from 1948–1973 and then generally diverged from 1974–2014.
  • the same price index, average labor productivity and hourly compensation increased at the same rate from 1948–2004, diverged and converged during 2005–2008, and generally diverged from 2009–2016:
Average Productivity and Hourly Compensation

[184]

Income Inequality

Overview & Trends

* From 1979 to 2013, the inflation-adjusted income of U.S. households rose by an average of 55%. For various income groups, it grew as follows:

Inflation-Adjusted Income Growth by Income Group

[185] [186]

* From 1979 to 2013, the inflation-adjusted income of U.S. households after federal taxes rose by an average of about $29,800 or 59%. For various income groups, it grew as follows:

Inflation-Adjusted Household Income After Federal Taxes

Income Group

1979

2013

Increase From 1979–2013

Dollars

Percent

Lowest 20%

$16,800

$24,500

$7,700

46%

Second 20%

$31,700

$43,400

$11,700

37%

Middle 20%

$45,000

$60,800

$15,800

35%

Fourth 20%

$58,900

$86,100

$27,200

46%

Highest 20%

$103,700

$195,300

$91,600

88%

Top 1%

$355,100

$1,037,500

$682,400

192%

All Groups

$50,400

$80,100

$29,700

59%

[187] [188]

* From 1979 to 2013, U.S. middle-income households’ share of total income after federal taxes decreased by about 1.3 percentage points, or by 8%. The share of income for other groups changed as follows:

Share of Total Income After Federal Taxes

Income Group

1979

2013

Change

Percentage Points

Percent

Lowest 20%

7.4%

6.2%

–1.2

–16%

Second 20%

12.3%

10.7%

–1.6

–13%

Middle 20%

16.5%

15.2%

–1.3

–8%

Fourth 20%

22.2%

21.0%

–1.2

–5%

Highest 20%

42.0%

48.5%

6.5

15%

Top 1%

7.4%

12.4%

5.0

68%

[189] [190]


GINI Index

* The Gini index is the most common measure of income inequality.[191] [192] [193]

* Various reporters at major media outlets have cited the Gini index for household income to claim that:

  • “the gulf between high earners and low earners remains the widest it’s been since at least 1993, the earliest year for which there is comparable data.”[194]
  • income inequality is at a “record high.”[195]
  • “American inequality has increased significantly.”[196]

* A 2014 study published by the Social Science Research Network found that:

  • the average number of people per U.S. household has been declining for decades, and this accounts for “the reported increase” in the Gini index.
  • when the household data is “corrected for actual decrease in the average household size,” the index is comparable to the level for individual incomes.[197]

* Between 1940 and 2016, the number of households in the U.S. increased by 260%,[198] while the U.S. population increased 145%.[199] During this same period, the portion of unmarried or non-family households rose from 24% to 52%:

Married and Unmarried Households

[200]

* From 1967 to 2011:

  • the Gini index for persons in the U.S. has not varied by more than 2%.
  • the Gini index for households has risen by 20% due to family fragmentation that has spread workers’ wages over an increasing number of households:
Gini Index for Households and Persons

[201]

* The Gini index based on Census Bureau cash household income does not capture all income and taxes.[202] From 1979 to 2003, the Census Bureau published Gini data based on more comprehensive measures of household income. These measures account for numerous forms of income and taxes that are not included in the standard measure.[203] [204] Over this period, the Gini index for households based only on cash income averaged 12% higher than the index based on the most comprehensive Census income measure:

Gini Index for Households by Census Income Definition

[205]


Politicians & Media

* During his acceptance speech at the 2016 Republican National Convention, Donald Trump made the following claim, and New York Times and NPR reported that it was “true”:

Household incomes are down more than $4,000 since the year 2000.[206] [207] [208]

* This claim is based on data from the U.S. Census Bureau,[209] which:

  • is “based solely on money income” and does “not include the value of noncash benefits,” such as food stamps, health benefits, subsidized housing, and “full or partial payments by business for retirement programs.”[210]
  • excludes “certain money receipts such as capital gains.”[211]
  • uses the Consumer Price Index to adjust for inflation.[212]
  • fails to account for 20% of middle-class household income in 2000 and 24% in 2013.[213]

* Comprehensive income data published by the Congressional Budget Office shows that inflation-adjusted median household income climbed by $4,900 between 2000 and 2013.[214]

* To adjust income data for inflation, the Congressional Budget Office uses the Personal Consumption Expenditure price index.[215] [216] If it adjusted for inflation using the Consumer Price Index, this same data would show that from 2000 to 2013, median income rose by $1,523 and median income after federal taxes rose by about $5,009.[217] [218]


* In 2015, U.S. Senator Elizabeth Warren of Massachusetts made the following claim, and PolitiFact said it was “mostly true”:

Well, since 1980, guess how much of the growth in income over the last 32 years—how much of the growth in income did the 90 percent get? Zero. None. Nothing. In fact, it is worse than that. The average family not in the top 10 percent makes less money today than they were making a generation ago.[219]

* Comprehensive income data from the Congressional Budget Office shows that the average inflation-adjusted income of households in the bottom 90% was:

  • $49,659 in 1980.
  • $70,806 in 2013, or an increase of 43% since 1980.[220] [221]

* In 2013, the Pew Research Center claimed that:

  • “U.S. income inequality has been increasing steadily since the 1970s, and now has reached levels not seen since 1928.”
  • in 2012, the top 1% received “nearly 22.5% of all pretax income, while the bottom 90%’s share is below 50% for the first time ever.”[222]

* Comprehensive income data from the Congressional Budget Office shows that in 2012, the top 1% received 17% of pretax income, and the bottom 90% received 61%. The distribution of pretax income from 1979–2013 varied as follows:

Share of Pretax Income

[223] [224]


Piketty & Saez

* The claims above from Elizabeth Warren, PolitiFact, and Pew Research are based on the work of Ph.D. economists Thomas Piketty and Emmanuel Saez.[225] [226] Paul Krugman of the New York Times has called their work on income inequality a “landmark piece of research that has had a major impact.”[227]

* The income data presented by Piketty and Saez overstates income inequality by:

  • excluding government benefits, which are 20% of income for the bottom 90% of households and 3% of income for the top 10% of households.[228] [229]
  • excluding non-cash market income (like healthcare benefits and employer contributions to retirement plans), which is 6% of income for the bottom 90% and 4% of income for the top 10%.[230] [231]
  • excluding most federal taxes, which effectively lowers the income of the bottom 90% by 14% and lowers the income of the top 10% by 27%.[232] [233] [234]
  • determining income based on tax units—“the group of individuals who file a tax return together and their child dependents”—instead of households. This reduces the income growth of the bottom 90% relative to the top 10% by failing to account for additional persons and incomes in the household.[235] [236] [237]
  • does not account for the rising portion of unmarried or nonfamily households, which grew from 28% in 1967 to 52% in 2013. [238] This reduces the income growth of the bottom 90% relative to the top 10%.[239]

* According to Piketty and Saez, from 1979 to 2013, the pre-tax income share of the top 10% grew by 12 percentage points. Comprehensive income data from the Congressional Budget Office show that the income share of the top 10% after federal taxes grew by 7 percentage points during this period:

Top 10% Income Share: Piketty & Saez Versus Congressional Budget Office

NOTE: This chart does not account for the rise in number of households, which would reduce the income share growth of the top 10% over time.[240]

[241] [242]


* In 2006, Piketty and Saez claimed that “the average Federal tax burden on top 1% families has decreased from 44.4% in 1980 to 30.4% in 2004,” or by 14 percentage points.[243]

* Comprehensive tax and income data from the Congressional Budget Office shows that the average federal tax burden on top 1% of households:

  • decreased from about 33% in 1980 to 30% in 2004, or by three percentage points.
  • increased from about 33% in 1980 to 34% in 2013, or by one percentage point.[244] [245]

* In 2006, Piketty and Saez claimed that when comparing federal taxes and government benefits from 1980 to 2004, the “decrease in taxes at the top [1%] outweighs the increase in benefits at the bottom.”[246]

* Comprehensive inflation-adjusted tax and government benefit data from the Congressional Budget Office shows that from 1980 to 2004:

  • the average federal tax burden on the top 1% declined by about 9%, which equates to a total decrease of $51 billion for this group.
  • average government benefits for the 99% rose by 156%, which equates to a total increase of $753 billion for this group.[247] [248]

Viewpoints

* In 1997, the Journal of Economic Behavior & Organization published a survey of 247 faculty, students, and staff at the Harvard School of Public Health. This survey:

  • asked participants if they would prefer to live in a world where:
    • A) “your current yearly income is $50,000” while “others earn $25,000,” or
    • B) “your current yearly income is $100,000” while “others earn $200,000.”
  • told respondents that “prices are what they are currently and prices (therefore the purchasing power of money) are the same in states A and B.”
  • found that “approximately 50 percent of the respondents preferred a world in which they had half the real purchasing power, as long as their relative income position was high.”[249]

Correlates of Income

NOTE: When interpreting the facts in this section, it is important to realize that correlation does not prove causation. This is because numerous factors can affect economic outcomes such as income, and there is frequently no objective way to identify, measure, and determine the interplay between all of them.

* Per an academic textbook about analyzing data:

Association is not the same as causation. This issue is a persistent problem in empirical analysis in the social sciences. Often the investigator will plot two variables and use the tight relationship obtained to draw absolutely ridiculous or completely erroneous conclusions. Because we so often confuse association and causation, it is extremely easy to be convinced that a tight relationship between two variables means that one is causing the other. This is simply not true.[250] [251] [252]

Education

* In 2017, the average cash earnings of U.S. residents aged 25–64 with different levels of formal education varied as follows:

Average Cash Earnings of People 25–64

[253] [254]

* In 2017, 79% of U.S. residents aged 25–64 had at least some cash earnings, and 21% did not have any cash earnings. For varying levels of education, the rates varied as follows:

Portion of People Aged 25–64 with Cash Earnings

[255]

* In 2016, nine of the top-10 highest-paying occupations were in the medical or dental fields.[256]

* For more facts about education and income, visit Just Facts research on education.


Public-Sector Corruption

* In 2011, the EPPI-Centre at the University of London published a systematic review of 115 corruption studies which found that “corruption has negative and statistically significant effects on [economic] growth—directly and indirectly.”[257] [258]

* Gross Domestic Product (GDP) is the most common measure of a nation’s economic output.[259] It measures the value of all “goods and services produced within a country’s geographic borders.”[260]

* Per the textbook Microeconomics for Today (and other academic sources):

GDP per capita provides a general index of a country’s standard of living. Countries with low GDP per capita and slow growth in GDP per capita are less able to satisfy basic needs for food, shelter, clothing, education, and health.[261] [262] [263]

* Based on data from more than 145 countries, GDP per person is generally higher in countries with greater public-sector transparency and accountability:

GDP Per Person and Public-Sector Transparency & Accountability

[264] [265] [266] [267]


Natural, Produced & Human Resources

* Nations have three primary types of resources or wealth:

  • Natural capital, which includes:
    • cropland, pastureland, and forested areas.
    • non-renewable resources, such as oil, natural gas, and minerals.[268]
  • Produced capital, which includes:
    • technology, machinery, and other equipment.
    • structures, such as buildings and roads.[269]
  • Intangible capital, which includes:
    • human capital, such as skills and know-how.
    • social capital, or “trust among people in a society and their ability to work together for a common purpose.”
    • efficient and effective governance.[270]

* In 2006, the World Bank analyzed the capital resources of 118 nations and found that the wealth of most nations is mainly comprised of intangible capital. In about 85% of these countries, intangible capital accounted for more than half of their wealth.[271] Per the study:

  • “rich countries are largely rich because of the skills of their populations and the quality of the institutions supporting economic activity.”
  • “if an economy has a very efficient judicial system, clear property rights, and an effective government, the result will be a higher total wealth….”[272]

* In 2005, the capital resources of nations with the highest and lowest wealth per person varied as follows:

Total Wealth Top and Bottom 10 Countries, 2005

Rank

Country

Wealth Per Person (PPP)

Capital

Natural

Produced

Intangible

Top 10 Countries

1

Luxembourg

$779,601

$5,805

$203,387

$570,409

2

Kuwait

$765,219

$618,083

$168,548

–$21,412

3

United States

$734,195

$13,692

$99,137

$621,367

4

United Arab Emirates

$728,889

$291,256

$175,427

$262,207

5

Brunei Darussalam

$657,376

$1,087,550

$438,724

–$868,898

6

Norway

$616,547

$82,291

$136,760

$397,496

7

Iceland

$593,380

$7,730

$85,959

$499,690

8

Singapore

$555,934

$4

$183,775

$372,155

9

Switzerland

$543,986

$7,511

$132,137

$404,337

10

Canada

$537,878

$36,665

$89,182

$412,031

Bottom 10 Countries

142

Ethiopia

$13,876

$4,406

$1,272

$8,198

143

Sierra Leone

$13,061

$4,110

$758

$8,194

144

Niger

$12,312

$3,767

$1,017

$7,529

145

Chad

$12,078

$10,205

$2,878

–$1,005

146

Liberia

$10,631

$6,702

$454

$3,475

147

Guinea-Bissau

$10,464

$5,010

$1,456

$3,998

148

Mozambique

$9,807

$2,115

$1,199

$6,492

149

Burundi

$9,388

$10,840

$666

–$2,118

150

Malawi

$9,261

$2,916

$1,315

$5,030

151

Congo, Dem. Rep.

$5,127

$3,309

$414

$1,403

[273] [274]


Marriage

* Between 1947 and 2016, the portion of unmarried or nonfamily households in the U.S. rose from 22% to 52%:

Unmarried or Nonfamily Households in the U.S.

[275]

* In 2015, the median household cash income for U.S. households with different marital statuses varied as follows:

Median Household Cash Income by Marital Status

[276] [277] [278] [279]

* In 2011, the median cash income of U.S. households with children:

  • was $57,100.
  • headed by a single mother who was divorced, separated, or widowed was $29,000.
  • headed by a single mother who has never married was $17,400.[280] [281]

* Between 1960 and 2011, the share of single mothers who have never married rose from 4% to 44%.[282]

* From 1949 to 2015 the median inflation-adjusted cash income of married-couple families in the U.S. rose by more than 200%. The change in income for other types of families varied as follows:

Inflation-Adjusted Median Income by Family Type

[283] [284]


Gender

* In 2015, full-time, year-round female workers earned median cash wages of $39,940. This was 20% less than the $49,938 earned by males.[285] [286]

* During his 2014 State of the Union address, President Barack Obama stated:

Today, women make up about half our workforce. But they still make 77 cents for every dollar a man earns. That is wrong, and in 2014, it’s an embarrassment. A woman deserves equal pay for equal work.[287] [288]

* Obama’s statement does not account for the following factors that pertain to “equal pay” and “equal work”:

  • Full-time male workers average 6% more workdays per year and 5% more workhours per workday than full-time female workers.[289]
  • Men are more likely than women to pursue technically demanding and higher-paying careers, such as computer science, finance, and engineering.[290] [291] [292]
  • Women are more likely than men to temporarily leave their careers to raise a family, resulting in less work experience and continuity.[293] [294]
  • Women are more apt than men to select jobs that offer higher fringe benefits in exchange for less cash wages.[295] [296]
  • More than 28% of U.S. workers are in physically challenging occupations (such as construction, law enforcement, firefighting, and the military), and most men have significantly greater muscular strength and cardiovascular endurance than most women.[297] [298]

* Various studies that have attempted to account for some (but not all) of the factors above have found:

[A]fter we controlled for all the factors included in our analysis that we found to affect earnings, college-educated women working full time earned an unexplained 7 percent less than their male peers did one year out of college.
– American Association of University Women, 2012[299]
Once we control for outside factors the wage gap between men and women shrinks considerably. Now women earn typical pay that is on average 98% of the typical pay for men by major. Occasionally, women may even earn more. Therefore, when looking at gender-specific pay by major for a controlled sample, the wage gap all but disappears.
– PayScale, 2009[300]
Our analysis of the gender pay gap is the first to include fringe benefits in a comprehensive measure of compensation for men and women. The results show that including fringe benefits makes a considerable difference in the analysis of earnings differentials. In fact, we conclude that any measure of earnings that excludes fringe benefits may produce misleading results as to the existence, magnitude, consequence, and source of market discrimination. For our sample of working men and women between the ages of 26 and 34 in 1990, the average female wage rate was 87.4% of the average male wage rate; but when an index of total compensation is used, the estimate rises to 96.4% of male compensation.
Industrial Labor Relations Review, 1995[301]

* Per a 2009 analysis of gender wage studies conducted for the U.S. Department of Labor by CONSAD Research Corporation:

It is not possible to produce a reliable quantitative estimate of the aggregate portion of the raw gender wage gap for which the explanatory factors that have been identified account. Nevertheless, it can confidently be concluded that, collectively, those factors account for a major portion and, possibly, almost all of the raw gender wage gap.[302]

Race

* In 2015, the median household cash incomes of different races and ethnicities in the U.S. varied as follows:

Median Household Cash Income

Race / Ethnicity

Median Income

Asian

$77,003

White

$60,000

Black

$36,583

Hispanic

$45,000

All Groups

$56,142

[303] [304] [305] [306]

* In 2015, the formal education levels of U.S. residents aged 25–65 with different races and ethnicities varied as follows:

Race / Ethnicity

Formal Education

No High School

Diploma

High School

Some College

Bachelor’s or

Higher

Asian

8%

17%

16%

59%

White

10%

27%

28%

35%

Black

11%

33%

31%

24%

Hispanic

30%

31%

22%

17%

[307] [308]

* In 2015, the median cash earnings of U.S. residents aged 25–65 with different levels of formal education, races, and ethnicities varied as follows:

Race / Ethnicity

Median Earnings (Thousands $)

High School

Bachelor’s or Higher

White

$24

$50

Asian

$20

$50

Hispanic

$20

$42

Black

$15

$44

[309] [310] [311] [312]

* In 2015, the portion of U.S. residents living in homes with married couples ranged from 72% for Asians to 37% for blacks:

U.S. Residents Living in Homes with Married Couples

[313] [314]

* In 2015, the median household cash incomes for U.S. households of different races, ethnicities, and marital statuses varied as follows:

Race / Ethnicity

Median Household Cash Income (Thousands $)

Married, Spouse Present

Divorced

Separated

Never Married

Asian

$99

$50

$48

$53

White

$85

$41

$33

$45

Black

$73

$33

$26

$29

Hispanic

$57

$38

$28

$37

All Groups

$85

$40

$32

$40

[315] [316] [317] [318]

* For more facts about race and income, visit Just Facts research on racial issues.


Immigration

* In 2015, the median cash income of families living in the U.S. was $61,805. This varied by immigration status and Hispanic origin as follows:

Family Cash Income by Immigration Status & Hispanic Origin

[319] [320]

* Male immigrants who arrived in the U.S. during:

  • 1965–69 earned an average of 24% less than native-born workers of the same age. Ten years later, they were earning 12% less. Twenty years later, they were earning 2% less. Forty years later, they were earning 18% more.
  • 1985–89 earned an average of 33% less than native-born workers of the same age. Ten years later, they were earning 27% less. Twenty years later, they were earning 25% less.
  • 1995–99 earned an average of 27% less than native-born workers of the same age. Ten years later, they were earning 27% less.[321]
Wage Assimilation of Male Immigrants By Year of Entry

[322]

* In 2013, 54% of Mexico and Central American immigrants aged 25–64 did not have a high school diploma or GED, as compared to 7% of people born in the U.S. in the same age group. The rates for other groups were as follows:

U.S. Residents Aged 25–64 Without a HS Diploma or GED

[323]

* A 2014 study by the Brookings Institution found that:

  • nearly one in 10 working-age U.S. adults … is considered limited English proficient.”
  • workers with limited English proficiency “earn 25 to 40 percent less than their English proficient counterparts.”[324]

* For more facts about immigration and income, visit Just Facts’ research on immigration.

Work

Overview

* One of the key factors that impact nations’ standards of living is their average hours of work per person.[325]

* Unpaid work—such as caring for children, cooking, and cleaning—increases standards of living, but it is often not recorded in standard economic measures.[326] [327] Per an academic book published by Stanford University Press:

The impact of declining levels of unpaid work over time on all aspects of household living standards deserves more careful consideration. There is something fundamentally misleading about measuring gains to family earnings provided by increases in women’s employment that do not account for the reduction in living standards resulting from declines in time devoted to unpaid work.[328]

* In July 2017, the employment status of the total U.S. civilian, non-institutionalized population was as follows:

  • 48% employed
  • 40% employed full-time
  • 8% employed part-time
  • 2% unemployed
  • 50% not in the labor force[329]

* In July 2017, the employment status of the U.S. civilian, non-institutionalized population aged 16 years and over was as follows:

  • 61% employed
  • 50% employed full-time
  • 11% employed part-time
  • 3% unemployed
  • 37% not in the labor force[330]

* In July 2017, the employment status of the U.S. civilian, non-institutionalized population aged 25–54 was as follows:

  • 78% employed
  • 69% employed full-time
  • 9% employed part-time
  • 3% unemployed
  • 18% not in the labor force[331]

* In 2015, 22% of employed adults worked multiple jobs or performed informal work in addition to their regular job.[332]


Labor Force Participation

* Per the Congressional Budget Office:

Labor force participation is an important component of economic growth: As more people participate in the labor force, firms are able to expand employment and increase production.
Greater labor force participation is associated with higher tax revenues because the number of employed people, and therefore the number of people paying income and payroll taxes, tends to rise. It is also associated with lower spending on means-tested programs (which provide cash payments or other forms of assistance to people with relatively low income or few assets), such as Medicaid, and on refundable tax credits.
Changes in the labor force participation rate can distort the significance of the unemployment rate—that is, the share of people in the labor force without a job—as a measure of the health of the economy. For example, between the end of the 2007–2009 recession and 2017, the unemployment rate for people ages 25 to 54 fell by 4.5 percentage points even though the share of that population with a job increased by just 3 percentage points. The unemployment rate declined partly because of an increase in the share of the population that was employed but also because of a decrease in the labor force participation rate.[333]

* The labor force, as defined by the Bureau of Labor Statistics, includes all people who are “either working or actively seeking work.” The potential labor force used by the Bureau to determine the labor force participation rate includes:

persons 16 years of age and older residing in the 50 states and the District of Columbia who do not live in institutions (for example, correctional facilities, long-term care hospitals, and nursing homes) and who are not on active duty in the Armed Forces.[334] [335]

* In 2016, men aged 35–44 had a labor force participation rate of 91%. This was the highest rate of all age and gender groups, which varied as follows:

Labor Force Participation Rate by Age and Gender

[336]

* Between 1976 and 2016, the portion of men in their prime working years (25–54) who were not in the labor force increased by 97%.[337] [338]

* Current labor force participation rates for men of all age groups are lower than they were in 1948, while the opposite is true for women:

Labor Force Participation Rates

[339]


Employment & Unemployment

* As defined by the U.S. Bureau of Labor Statistics, “employed” people are those who, over the course of a week:

  • work at least one hour as paid employees, or
  • work “in their own business, profession, or on their own farm,” or
  • work at least 15 hours as “unpaid workers in an enterprise operated by a member of the family, or
  • do not work but have jobs or businesses they are temporarily absent from due to:
    • vacation.
    • illness.
    • bad weather.
    • childcare problems.
    • maternity or paternity leave.
    • a labor-management dispute.
    • job training.
    • “other family or personal reasons.”[340]

* “Unemployed” people are those who are not working but are “available for work” and:

  • have made “specific efforts to find employment” in the prior four weeks, or
  • are waiting to be called back to a job after being laid off.[341]

* The federal unemployment rate is determined by dividing the number of unemployed people by the number of people in the labor force.[342] The labor force does not include:

  • retirees.
  • students.
  • people caring for children or family members.
  • “others who are neither working nor seeking work.”[343] [344]

* From 1947 to 2016, the annual unemployment rate peaked in 1982 at 9.7%. Over this period, the rate has varied as follows:

U.S. Unemployment Rate

[345]


Underemployment

* “Underemployment” is a wider measure of idle potential labor than unemployment. The broadest measure of underemployment published by the U.S. Bureau of Labor Statistics is called “U-6,” which includes:

  • the unemployed.
  • discouraged and marginally attached workers, who are people who are not working and have searched for work in the prior 12 months but not in the prior four weeks.
  • involuntary part-time workers, who are people who work less than 35 hours per week, would like to work full time and are available to do so, but don’t because of economic reasons, such hour cutbacks by their employers.[346] [347]

* From 1994 to 2016, the annual underemployment rate peaked in 2009 at 17.1%. Over this period, the rate has varied as follows:

U-6 Underemployment Rate

[348]


Work Hours

* During 2015, U.S. civilian residents aged 15 and over spent an average of 42% more time on leisure and sports than on work and work-related activities:

How U.S. Residents Spend Their Time

[349]

* During 2015, the U.S. residents of different age groups spent the following hours per day on various activities:

Activity

Average Hours Per Day Spent on Activities by Age Range

15–19

20–24

25–34

35–44

45–54

55–64

65–74

75+

Personal care

10.6

10.2

9.5

9.2

9.2

9.4

9.5

10.1

Leisure and sports

5.2

4.8

4.1

4.0

4.6

5.6

6.9

7.6

Educational

3.9

1.0

0.3

0.1

0.1

0.0

0.0

Working and work-related activities

1.2

4.2

4.9

5.1

4.8

3.7

1.3

0.4

Eating and drinking

1.0

1.0

1.2

1.2

1.1

1.2

1.3

1.4

Household activities

0.7

1.1

1.6

1.9

2.0

2.1

2.6

2.4

Purchasing goods and services

0.5

0.6

0.7

0.7

0.8

0.9

1.0

0.9

Other activities not elsewhere classified

0.3

2

0.2

0.2

0.2

0.2

0.3

0.3

Caring for and helping non-household members

0.2

0.2

0.1

0.1

0.2

0.4

0.4

0.2

Organizational, civic, and religious activities

0.2

0.1

0.2

0.3

0.3

0.4

0.5

0.5

Telephone calls, mail, and e-mail

0.2

0.1

0.1

0.1

0.1

0.2

0.2

0.3

Caring for and helping household members

0.1

0.3

1.0

1.2

0.5

0.1

0.1

0.1

[350]

* In 1890, U.S. manufacturing laborers worked an average of 60 hours per week,[351] as compared to 41 hours in 2016.[352]

* In the U.S. between 1948 and 2015, the average annual work hours per employee declined by 14%.[353] Over this period, work hours per employee and per person varied as follows:

Average Annual Work Hours

[354]

* In 2015, full-time workers averaged 7.6 hours of work per day on the days that they worked. This figure was higher on weekdays (8.0 hours) than on weekend days (5.6 hours).[355]

* A 2011 study published by U.S. Bureau of Labor Statistics found that:

  • when employees were asked how many hours they usually work or had worked the prior week, their estimates were larger than the amount of time recorded in their daily time diaries.
  • employee estimates of their work hours exceeded their diaries “by between 5 percent and 12 percent.”
  • the average gap between time estimates and diaries was larger for women than men.
  • “larger discrepancies tend to arise from respondents who estimate more hours in their workweek.”[356] [357] [358]

Employee Compensation

Determinants

* Some of the primary factors that determine employee compensation are:[359]

  • worker productivity.[360]
  • the law of supply and demand.[361]
  • government-mandated minimum and prevailing wages.[362]
  • employer ability to pay.[363]
  • government regulations.[364]
  • costs of living.[365]
  • bargaining power.[366]
  • job requirements.[367]

Benefits

* In the U.S. during December 2016, the average cost to employers for one hour of employee work was $34.90, with wages and salaries accounting for 68% of costs, and benefits accounting for 32% of costs.[368]

* Per the U.S. Department of Labor, “In the final four decades of the 20th century, employee compensation, as measured by employer costs, has undergone dramatic shifts” from cash to benefits. Many of these benefits are “legally required” by government, such as Social Security and Medicare.[369]

* Government mandates that force employers to pay for programs like Social Security, Medicare, and the Affordable Care Act [ACA] reduce cash wages for employees. Per the:

  • Congressional Budget Office, “the employers’ share of payroll taxes is passed on to employees in the form of lower wages.”[370] [371]
  • Government Accountability Office, “employees bear the entire burden of social insurance taxes in the form of reduced wages.”[372]
  • Tax Policy Center, “the employer portion of payroll taxes translate into lower wages.”[373]
  • American Health Policy Institute, “The cost of the ACA to large U.S. employers (10,000 or more employees) is estimated to be between $4,800 to $5,900 per employee” during 2013 to 2023.[374] [375]

* Adjusted for inflation, employers’ average hourly costs for employee compensation rose at the following rates over the time periods below:

Inflation-Adjusted Hourly Cost Growth of Employee Compensation

Category

Private Sector
(1986–2016)

State and Local
Government
(1991–2016)

Wages & Salaries

23%

22%

Benefits

45%

64%

Total

29%

35%

[376]

* In December 2016, the components of compensation for private industry employees were as follows:

Employer Hourly Costs for Private Industry Employees

[377]


Overtime

* The U.S. Department of Labor regulates overtime pay, which is 1.5 times an employee’s hourly rate for hours worked over forty hours.[378]

* Executive, administrative and professional workers are among those employees who are exempt from overtime pay regulations.[379]

* In the 2000s, three employees brought a class action lawsuit against IBM for withholding overtime pay from workers that IBM considered to be exempt from the regulations. The company settled the lawsuit for $65 million.[380] [381]

* To prevent future lawsuits, IBM converted 7,000 salaried employees into hourly employees and decreased their base pay by 15% to offset the anticipated overtime costs.[382]


* In 2015, the U.S. Department of Labor, then under the leadership of Barack Obama,[383] issued a regulation to make overtime pay mandatory for workers earning less than $47,476/year. This was double the previous threshold of $23,660.[384] [385]

* Obama’s regulation was scheduled to take effect on December 1, 2016,[386] but a federal judge granted an injunction before it was implemented.[387]

* In 2017, a federal judge appointed by Obama struck down this regulation,[388] and the Trump administration decided to not appeal this ruling.[389]


Minimum Wage

* In 1931, the 71st U.S. Congress and Republican President Herbert Hoover enacted the first federal minimum wage law. It required contractors engaged in federal construction projects in excess of $5,000 dollars to pay workers a “prevailing wage.”[390]

* In 1938, the 75th Congress and Democratic President Franklin D. Roosevelt enacted a law that required all employers to pay a minimum wage to most employees “engaged in commerce or in the production of goods for commerce.”[391]

* The 1938 law set the federal minimum wage at $0.25 per hour. Adjusted for inflation, this is equivalent to $4.34 in 2017 dollars.[392] [393]

* Since 1938, various federal laws have increased the minimum wage more than 20 times. The latest increase, in July of 2009, brought the minimum wage to $7.25 per hour.[394]

* Federal minimum wage law has exceptions that “apply under specific circumstances to workers with disabilities, full-time students, youth under age 20 in their first 90 consecutive calendar days of employment, tipped employees and student-learners.”[395]

* Excluding tips, commissions, and overtime pay, 3% of all employees in the U.S. were paid at or below the federal minimum wage in 2016. The rates for different age groups varied as follows:

U.S. Employees Paid at or Below Minimum Wage

Age Group

Total

Portion

16 to 19 Years

4,592,000

10%

20 to 24 Years

11,264,000

5%

25 Years and Older

64,026,000

2%

[396]

* Per the U.S. Bureau of Labor Statistics:

The industry with the highest percentage of workers earning hourly wages at or below the federal minimum wage was leisure and hospitality (about 13 percent). Three-fifths of all workers paid at or below the federal minimum wage were employed in this industry, almost entirely in restaurants and other food services. For many of these workers, tips may supplement the hourly wages received.[397]

* In 2016, part-time hourly employees—those who worked 34 hours or less—accounted for 54% of employees at or below the federal minimum wage.[398]

* A 2014 study by the Congressional Budget office found that increasing the minimum wage from $7.25 to $10.10 per hour will:

  • raise the average income of families below the poverty line by 3%.
  • give 19% of the resulting salary increases to families below the poverty threshold.
  • give 81% of the salary increases to families above the poverty line.
  • give 29% of the increase to families earning more than three times the poverty line.
  • raise prices for consumers.[399]

* The portion of employees at or below federal minimum wage peaked at 15% in 1980 and 1981. It has since varied as follows:

Portion of Hourly Workers at or Below Minimum Wage

[400]


* Per a 2013 working paper by Ph.D. labor economists David Neumark, J.M. Ian Salas, and William Wascher:[401] [402] [403]

  • The debate “about the economic effects and the merits of the minimum wage date back at least as far as the establishment of the Department of Labor as a cabinet-level agency in 1913.”
  • Over time, empirical studies “especially the time-series studies conducted in the 1960s and 1970s, increasingly found that minimum wages tended to reduce employment among teenagers, who were viewed as a proxy for low-skilled labor.” Thus, economists “began to coalesce around the idea that minimum wages have adverse effects on low-skilled employment.”
  • The “debate over the employment effects of the minimum wage reemerged in the early 1990s” after the publication of four studies that “formed the basis for what is sometimes termed the ‘new minimum wage research.’ ” These studies “were diverse in their findings, ranging from:”
    • a negative effect on employment, to
    • no effect on employment, to
    • a positive effect on employment.[404]

* In 2007, the journal Foundations and Trends in Microeconomics published a review of the “new minimum wage research” that examined 102 studies. This review found that:

  • the new studies produced a “wide range of estimates of the effects of the minimum wage on employment.”[405]
  • the frequent “assertion that the new minimum wage research fails to support the conclusion that the minimum wage reduces the employment of low-skilled workers is clearly incorrect.” Nearly two thirds of the 102 studies “give a relatively consistent (although by no means always statistically significant) indication of negative employment effects of minimum wages.”[406]
  • when “researchers focus on the least-skilled groups most likely to be adversely affected by minimum wages the evidence for” the negative effect on employment “seems especially strong.”[407]
  • there were “very few—if any—cases where a study provides convincing evidence of positive employment effects of minimum wages.”[408]

* As of January 1, 2017, at the state level:

  • Two states have minimum wage levels lower than the federal government (federal law applies).
  • Five states have no minimum wage laws (federal law applies).
  • Fourteen states have wages equal to federal law.
  • 29 states and the District of Columbia have wages that exceed federal law (state law applies).
  • The District of Columbia has the highest minimum wage, $11.50 per hour. Massachusetts and Washington follow at $11.00 per hour.[409] [410]

* In 2015, the Los Angeles Federation of Labor, a labor union, helped lead an effort to increase the minimum wage in L.A. to $15/hour by 2020. After the City Council passed the bill, the same labor union lobbied to change it so that companies with union workers would be exempt from the law.[411]

* For more facts about the effects of governments forcing employers to pay wages that are above market rates, visit Just Facts’ research on unions.


Government Employees

* In 2016, federal, state and local governments spent $1.9 trillion on employee compensation. This amounts to an average of $15,176 from every household in the United States.[412] [413] [414] [415] [416] [417]

* In 2014, 23.1 million people—excluding those at the Central Intelligence Agency, the National Security Agency, and the Defense Intelligence Agency—worked for federal, state, and local governments. This amounts to 16% of all employees in the United States.[418]

* In 2017, the Congressional Budget Office published a study comparing the compensation of full-time, year-round private sector workers to non-postal, civilian, federal workers in 2011 to 2015. The study accounted for education, occupation, work experience, geographic location, employer size, and various demographic characteristics. The study found that:

  • federal workers received an average of 17% more compensation than comparable private sector workers.
  • across various education levels, federal employee compensation premiums ranged from a low of –18% for workers with a professional degree or doctorate to a high of 53% for workers with a high school diploma or less:

Federal Employee Compensation Premiums Relative to Private Sector

Formal Education

Wages

Benefits

Total

High School Diploma or Less

34%

93%

53%

Some College

22%

80%

39%

Bachelor’s Degree

5%

52%

21%

Master’s Degree

–7%

30%

5%

Professional Degree or Doctorate

–24%

–3%

–18%

All Levels of Education

3%

47%

17%

[419]

* Private-sector businesses must compete for customers, and this limits employee compensation and owner profits.[420] [421] Such competition is lessened in the public sector, because governments often have monopolies over certain services, such as law enforcement and public schools. Per the U.S. Supreme Court’s unanimous decision in Abood v. Detroit Board of Education:

A public employer, unlike his private counterpart, is not guided by the profit motive and constrained by the normal operation of the market. Municipal services are typically not priced, and where they are they tend to be regarded as in some sense “essential” and therefore are often price-inelastic [i.e., the demand for the service is not affected by its price[422]].
Although a public employer, like a private one, will wish to keep costs down, he lacks an important discipline against agreeing to increases in labor costs that in a market system would require price increases. A public-sector union is correspondingly less concerned that high prices due to costly wage demands will decrease output and hence employment.[423]

* For more facts about government employee compensation, visit Just Facts’ research on unions.

Wealth

Overview

* Wealth, or net worth, is the value of assets minus debts.[424] [425]

* While income is “a flow of purchasing power,” wealth “refers to the value of accumulated assets at a given point in time.”[426] [427] [428]

* Assets include items such as:

  • checking and saving accounts.
  • mutual funds.
  • retirement accounts.
  • royalties.
  • proceeds from lawsuits and estates.
  • vehicles.
  • equity in property and businesses.
  • artwork.
  • jewelry.
  • precious metals and stones.
  • antiques and collectibles.[429]

* Per the Organization for Economic Cooperation and Development:

  • “Income and wealth are essential components of individual well-being.”
  • “Both income and wealth enhance individuals’ freedom to choose the lives that they want to live.”
  • “Wealth allows individuals to smooth consumption over time and to protect them from unexpected changes to income.”
  • “Households with reserves of wealth can also utilize these to generate income and to support a higher standard of living.”[430]

* Per the U.S. Census Bureau:

In times of economic hardship, such as unemployment, illness, or divorce, a person’s or household’s financial assets (e.g., savings accounts) are an additional source of income to help pay expenses and bills. For individuals and households with a householder 65 years and older, wealth is also an important source of post-retirement income.[431]

* In a 2015 survey of about 5,700 adults, 68% of working adults reported saving “at least a portion of their income in the prior year.”[432]


Data Sources

* Researchers generally consult two primary sources for information regarding the wealth of U.S. residents: the Federal Reserve’s Survey of Consumer Finances and Internal Revenue Service tax returns. The Congressional Budget Office and the Census Bureau also publish wealth data.[433] [434] [435] [436] [437] [438]

* These sources have varying strengths and weaknesses:

  • Neither the Survey of Consumer Finances nor the IRS data “fully identifies wealth across the nation’s entire distribution of wealth.”[439]
  • Congressional Budget Office and Survey of Consumer Finances data are the product of a cross-sectional studies—observations at a specific point in time. Thus, each survey “samples a different group of families,” taking “snapshots of family wealth” without providing “information about changes in the wealth of particular families over time.”[440]
  • The Census Bureau’s Survey of Income and Program Participation is a longitudinal survey that documents changes that occur in the lives of specific people over time.[441]
  • The limited demographic information in IRS data “precludes researchers from identifying the distribution of family wealth on the basis of age or education.”[442]
  • Tax return data requires analysts to make assumptions, based on yearly income, to estimate levels of wealth.[443]
  • IRS data “cannot account for people who do not file tax returns.”[444]
  • Congressional Budget Office data does not account for assets “such as defined benefit pension plans and future Social Security benefit payments,” which “significantly understates the resources” of some families. This exaggerates the concentration of wealth at the top of the distribution.[445]

* The Survey of Consumer Finances found that the inflation-adjusted median family net worth of the top 10% of the wealth distribution increased by 59% from 1989 to 2013. The change in net worth for the other wealth groups varied as follows:

Change in Median Family Net Worth by Wealth Group

[446] [447]

* Per the Federal Reserve Board’s Survey of Consumer Finances:

[P]atterns in net worth over the past decade were largely driven by the boom and bust in house and other asset prices. The bust, in particular, had a disproportionate effect on families in the middle of the net worth distribution, whose wealth portfolio is dominated by housing.[448]

* Per the Congressional Budget Office:

[F]or those in the 26th to 50th percentiles between 1989 and 2007, the decline in wealth associated with the [2007] recession more than offset earlier increases…. For those families, increases in home equity and in financial and other assets contributed to rising wealth between 1989 and 2007, and conversely, losses in home equity and in financial and other assets after 2007 contributed to the decline in average wealth over the period.[449]

* Congressional Budget Office data shows that the median inflation-adjusted family wealth of all age groups decreased during the Great Recession, and as of 2013, had not rebounded:

Inflation-Adjusted Median Family Wealth by Age Group

[450] [451]

* U.S. Census Bureau data shows that in 2013, the median net worth of a householder with a bachelor’s degree (and no further education) was $147,578. The net worth of people with other levels of educational attainment varied as follows:

Median Net Worth by Educational Attainment

[452]

* Congressional Budget Office data shows that between 1989 and 2013, inflation-adjusted median family wealth:

  • rose by 48% for families headed by someone with a graduate degree.
  • slightly declined for families headed by someone without a bachelor’s degree:
Inflation-Adjusted Median Wealth by Education

[453] [454]


Mobility

* Per the Congressional Budget Office:

There are significant differences in wealth among different age … groups. In 2013, the median family wealth of families headed by someone who was age 65 or older—$211,000—was more than 3½ times the median wealth of families headed by someone between the ages of 35 and 49.[455]

* The Congressional Budget Office and the Survey of Consumer Finances provide “a series of snapshots of family wealth” rather than “information about changes in the wealth of particular families over time.”[456]

* It is possible to approximate changes in the net worth of particular families over time. For example, many of the 25–34 year-olds interviewed for the 1983 Survey of Consumer Finances were aged 35–44 in the 1992 survey (notwithstanding the deceased and migrants). Between 1983 and 2010, this group of families increased their median inflation-adjusted net worth by 27 times:

Inflation-Adjusted Median Family Net Worth by Age of Head

[457]


Home Ownership

* Per the Department of Housing and Urban Development:

[H]omeownership is widely believed to provide a variety of benefits for both individuals and communities. The benefits of homeownership for individuals include the ability to accumulate wealth through principal payments and asset appreciation and the ability to have greater control over their living environment. Owning a home results in greater investment by owners in their neighborhood and home because they are the recipients of changes in the value of the property.[458]

* Some of the downsides of owning a home can include:

  • maintenance time and costs.
  • significant upfront costs for down payment and closing.
  • financial losses if selling in a down market.
  • restricted job mobility.[459] [460] [461] [462]

* In 2015, 62% of U.S. households owned their home. Since 1901, home ownership rates have varied as follows:

U.S. Home Ownership Rate

[463] [464] [465]

Poverty

Measures & Definitions

* The U.S. government has two “slightly different” measures of poverty:

  1. Census Bureau poverty thresholds.
  2. Department of Health and Human Services (HHS) poverty guidelines.[466]

* Census poverty thresholds are used to calculate official estimates of the number of people in poverty.[467] [468]

* Per HHS, its:

poverty guidelines are a simplified version of the federal poverty thresholds used for administrative purposes—for instance, determining financial eligibility for certain federal programs. They are issued each year in the Federal Register by the Department of Health and Human Services.[469]

* In 2016, the Census poverty thresholds and HHS poverty guidelines for families or households of different sizes varied as follows:

2016 Poverty Measures

Family/Household

Census Thresholds*

HHS Guidelines

1 Adult, No Children

$12,486

$11,880

1 Adult, 1 Child

$16,543

$16,020

1 Adult, 2 Children

$19,337

$20,160

1 Adult, 3 Children

$24,424

$24,300

2 Adults, No Children

$16,072

$16,020

2 Adults, 1 Child

$19,318

$20,160

2 Adults, 2 Children

$24,339

$24,300

2 Adults, 3 Children

$28,643

$28,440

* Householder under age 65

† 48 Contiguous States and the District of Columbia

[470] [471]

* Census Bureau cash income estimates do not fully account for all income, because they:

  • are based on self-reported surveys in which respondents tend to underreport certain types of income.[472] [473]
  • fail to include benefits such as Medicare, Medicaid, public housing, food stamps, and employer fringe benefits.[474]

* In 2013, Census Bureau cash income estimates excluded 20% of the income of all households and 32% of income in the bottom 20% of households.[475] [476] [477] [478] This results in lower apparent income levels and higher poverty rates than measures that account for more income sources.[479] [480]

* Census Bureau estimates of total cash income earned in the U.S. during 2001 were $2.2 trillion lower than a more comprehensive measure of income estimated by the U.S. Bureau of Economic Analysis.[481] This amounts to $20,627 (in 2001 dollars) for every household in the United States.[482]

* Per a 2015 paper in the Journal of Economic Perspectives:

The underreporting of transfer income [government benefits] in surveys has profound implication for our understanding of the low-income population and the effect of government programs for the poor. … [T]his underreporting leads to:
  • “understatement of incomes at the bottom.”
  • recipients recorded as not receiving benefits.
  • understatement of “the poverty-reducing effects of government programs.”
  • “overstatement of poverty and inequality.”[483]

Eligibility for Welfare Programs

* Various government agencies use the HHS poverty guidelines—or multiples of them—to determine eligibility for at least 31 means-tested programs.[484] Eligibility for the programs below is based on the applicant’s income being at or under the following percentages of the HHS poverty guidelines:

  • 130% – Supplemental Nutrition Assistance Program (a.k.a. Food Stamps)[485]
  • National School Lunch Program
    • 130% – Free lunch
    • 185% – Reduced-price lunch[486]
  • 150% – Low Income Home Energy Assistance Program[487]
  • 185% – Women, Infants, and Children[488]
  • 400% – Affordable Care Act (Obamacare) health insurance exchanges[489]

* The following programs use other criteria instead of the HHS guidelines:

  • Supplemental Security Income
  • Earned Income Tax Credit
  • State/local-funded General Assistance (in most cases)
  • Some parts of Medicaid
  • Section 8 low-income housing assistance
  • Low-rent public housing[490]

* Per the U.S. Government Accountability Office:

[F]ederally funded programs for low-income people vary significantly with regard to who is eligible, how income is counted and the maximum income applicants may have to be eligible, and the benefits provided.[491] [492] [493]

* Since 1975, the portion of the U.S. population at or below the federal poverty line has ranged from a high of 15.2% in 1983 to a low of 11.3% in 2000. The portion of the population whose incomes were at or below 50%, 150%, and 200% of the poverty line varied as follows:

Portion of People by Ratio of Income to Poverty Level

[494] [495]

* In 2015, adults aged 18–64 accounted for 57% of people in poverty. Children under the age of 18 and people above 65 years comprised 34% and 10%, respectively. From 1966 to 2015, the portion of the U.S. population in poverty varied by age as follows:

Age Distribution of People in Poverty

[496] [497]


Welfare Trends

* In 1964, Democratic President Lyndon B. Johnson gave a State of the Union speech in which he declared an “unconditional war on poverty.” He stated that this war would:

  • “not only … relieve the symptom of poverty but … cure it, and above all … prevent it.”
  • be “a joint federal-local effort.”
  • “be done without any increase in spending.”
  • create or expand the following initiatives:
    • an “area redevelopment program”
    • “youth employment legislation”
    • “a broader Food Stamp program”
    • “a national service corps”
    • “unemployment insurance”
    • “minimum wage laws”
    • “special school aid funds”
    • building “libraries … hospitals and nursing homes”
    • training “nurses”
    • “hospital insurance for older citizens”
    • “help to those displaced by slum clearance”
    • “housing for our poor and our elderly”
    • “mass transit”
    • “the most far-reaching tax cut of our time”[498]

* Between 1968 and 2004, average inflation-adjusted federal, state, and local government spending per U.S. resident on means-tested welfare multiplied by more than four times:

Inflation-Adjusted Government Spending on Means-Tested Welfare

[499]

* In 2017, the federal government spent $701 billion on means-tested welfare.[500] This amounts to:

  • 18% of all federal outlays.[501]
  • $2,152 for every person living in the U.S.[502]
  • $5,554 for every household in the U.S.[503]
  • 3.6% of the U.S. gross domestic product.[504]

* In 2012, 135 million people—or 40% of the non-institutionalized population—were eligible for benefits from at least one of the nine major federal needs-tested welfare programs (excluding Medicaid). Per the Congressional Research Service:

An estimated 106 million persons (1 in 3 persons in the population) actually received benefits from one of these programs in 2012.[505]

* From 1994 to 2015, the portion of the U.S. population who lived in households where at least one person received any form of means-tested federal welfare rose from 27% to 36%. The portion who lived in households that received specific forms of means-tested federal welfare varied as follows:

Portion of U.S. Population Living in Households Receiving Federal Welfare

[506] [507]

* In 2015, total federal spending on low-income programs amounted to $848 billion. The majority of that spending was for healthcare. The portion of spending per category varied as follows:

Federal Spending on Low-Income Programs by Category

[508]

* From 1994 to 2016, inflation-adjusted Medicaid spending rose from an annual average of $457 for every person in the U.S. to $1,229. Spending per person in the U.S. on the top four federal welfare programs varied as follows:

Inflation-Adjusted Spending Per Person in the U.S. on the Top Four Federal Welfare Programs

[509]


Correlates

NOTE: When interpreting the facts in this section, it is important to realize that correlation does not prove causation. This is because numerous factors can affect societal outcomes like poverty, and there is frequently no objective way to identify, measure, and determine the interplay between all of them.

* In 2015, the portion of the U.S. population aged 18–64 with incomes below Census poverty thresholds varied by work time as follows:

People Aged 18–64 in Poverty by Work Time, 2015

Type of Worker

Portion

Less Than 1 Week of Work

32%

Less Than Full-Time Year-Round Workers

16%

All Workers

6%

Full-Time Year-Round Workers

2%

[510]

* In 2015, 5% of married-couple families had incomes below Census poverty thresholds. The rates for other types of families varied as follows:

Families in Poverty by Type

[511]

* In 2015, the portion of children in families with incomes below Census poverty thresholds varied by their family structure as follows:

Children in Poverty by Family Structure, 2015

Kind of Family

Portion

Female Householder

43%

Male Householder

27%

Husband-Wife Family

10%

[512]

* In 2015, the portion of the U.S. population with incomes below Census poverty thresholds varied by race as follows:

People in Poverty by Race, 2015

Race

Portion

Black

24%

Hispanic

21%

White

12%

Asian

11%

[513]

* In 2015, the poverty rates for U.S. residents of different races, ethnicities, and marital statuses varied as follows:

Race / Ethnicity

Poverty Rate by Race, Ethnicity, and Marital Status, 2015

Married,

Spouse Present

Divorced

Separated

Never Married

White

5%

16%

25%

17%

Asian

6%

15%

23%

16%

Black

8%

25%

34%

29%

Hispanic

13%

21%

29%

26%

[514] [515] [516]

* For more facts about poverty and race, visit Just Facts’ research on racial issues.

* In 2015, the portion of the U.S. population aged 18–64 with incomes below Census poverty thresholds varied by immigration status as follows:

People Aged 18–64 in Poverty by Immigration Status, 2015

Nativity Status

Portion

Non-Citizen

21%

Native Born

12%

Naturalized Citizen

10%

[517]

* For more facts about poverty and immigration, visit Just Facts’ research on immigration.

* In 2015, the portion of the U.S. population aged 25 and older with incomes below Census poverty thresholds varied by educational attainment as follows:

People Aged 25 and Older in Poverty by Education, 2015

Educational Attainment

Portion

No High School Diploma

26%

High School, No College

13%

Some College, No Degree

10%

Bachelor’s Degree or Higher

5%

[518]

* For more facts about poverty and education, visit Just Facts’ research on education.

* In 2015, the portion of the U.S. population aged 18–64 with incomes below Census poverty thresholds varied by disability status as follows:

People Aged 18–64 in Poverty by Disability Status, 2015

Disability Status

Portion

With a Disability

29%

With No Disability

11%

[519]

Debt

Benefit & Harm

* Per the U.S. Census Bureau:

Debt is an important financial tool used by U.S. households to finance their purchases. Households often use their available credit in times of economic prosperity to finance large purchases—such as a home or a vehicle—or to pay for a household member’s education. Additionally, they may take on debt to help them get through a period of unemployment or to help pay for medical care.[520]

* Per a 2007 Federal Reserve Board working paper:

As illustrated by the recent developments among subprime mortgage borrowers, excessive accumulation of debt can, in some circumstances, lead to financial distress.
[T]he ability to borrow more easily or cheaply means that households with unreasonable expectations about future income or asset appreciation can take on more debt than may be appropriate.[521]

* The same Federal Reserve paper states that the increases “in debt-income ratios” make “some households more vulnerable to shocks to” incomes, interest rates, and asset prices.[522]

* Debt can be secured or unsecured.[523] Per the District of Oregon U.S. Bankruptcy Court:

A debt that is backed by real or personal property is a “secured” debt. A creditor whose debt is “secured” has a legal right to take the property as full or partial satisfaction of the debt. For example, most homes are burdened by a “secured debt.” This means that the lender has the right to take the home if the borrower fails to make payments on the loan.
If you simply promise to pay someone a sum of money at a particular time, and you have not pledged any real or personal property to collateralize [make secure] the debt, the debt is unsecured. For example, most debts for services and some credit card debts are “unsecured.”[524]

* Some of the consequences of failure to repay unsecured debt are:

  • lower credit ratings.
  • difficulty obtaining further credit.
  • “frequent calls from collection agencies.”
  • “debt collection lawsuits.”[525]

Personal

* In the second quarter of 2018, the average U.S. household owed $121,857 in consumer debt, such as mortgages and credit cards.[526]

* In 2013, 75% of U.S. families had some kind of debt. Among these families, the median debt was $60,400, and:

  • 41% had mortgages.
  • 38% had credit card balances.
  • 31% had vehicle loans.
  • 20% had education loans.
  • 5% had home equity loans.[527]

* The most common category of family debt in 2013 was for a primary residence. Other categories varied as follows:

Category of Family Debt 2013

[528]

* In 2013, the median ratio of debt payments to family income for families who carried debt was 16%. This varied by family income as follows:

Median Ratio of Debt Payments to Family Income

[529]

* During 1989 to 2013, the median ratio of family debt payments to income varied as follows:

Median Ratio of Family Debt Payments to Income

[530]

* In 2016, the Congressional Budget Office reported that the “increase in average indebtedness between 2007 and 2013 for families in debt was mainly the result of falling home equity and rising student loan balances.”[531]

* From 2007 to 2013, the portion of families whose total debt was greater than total assets increased from 8% to 12%.[532]

* From 1989 to 2013:

  • the inflation-adjusted average indebtedness of families in debt increased by 256%.[533]
  • the portion of debt payments for the purchase of a primary residence rose from 71% to 80%.
  • the portion of debt payments for other purchases varied as follows:
Composition of Other Family Debt

[534] [535]

* In 2012, the delinquency rate of student loan debt surpassed credit card debt and remains the most common type of delinquent debt. From 2003 to 2017, the balance of consumer loans more than 90 days delinquent varied as follows:

Balance of Consumer Loans 90+ Days Delinquent

[536] [537]


Bankruptcy

* Per the Administrative Office of the U.S. Courts:

Filing bankruptcy can help a person by discarding debt or making a plan to repay debts.
All bankruptcy cases are handled in federal courts under rules outlined in the U.S. Bankruptcy Code.
There are different types of bankruptcies, which are usually referred to by their chapter in the U.S. Bankruptcy Code.[538] [539]

* Per the Federal Trade Commission:

Although bankruptcy is one option to deal with financial problems, it’s generally considered the option of last resort. The reason: its long-term negative impact on your creditworthiness. Bankruptcy information (both the date of your filing and the later date of discharge) stays on your credit report for 10 years, and can hinder your ability to get credit, a job, insurance, or even a place to live.[540]

* In 2005, Congress passed and President Bush signed the Bankruptcy Abuse Prevention and Consumer Protection Act of 2005.[541] The purpose of the bill was to:

improve bankruptcy law and practice by restoring personal responsibility and integrity in the bankruptcy system and ensure that the system is fair for both debtors and creditors.[542]

* Congress passed this law in response “to many of the factors contributing to the increase in consumer bankruptcy filings,” such as the:

  • “lack of personal financial accountability.”
  • rapid increase of people who file bankruptcy repeatedly.
  • “absence of effective oversight to eliminate abuse in the system.”[543]

* The law mandated “the implementation and monitoring of”:

  • means testing “to prevent debtors who have the ability to repay their creditors” from being relieved of their debts.
  • debtor audits “to determine the accuracy of information provided by individuals filing for bankruptcy.”
  • required credit counseling and a debtor education course “before having debts discharged.”[544]

* In 2006, after the Bankruptcy Abuse Prevention and Consumer Protection Act of 2005 was implemented, personal bankruptcy filings dropped 71%. Filings from 2001–2016 varied as follows:

Personal Bankruptcy Filings

[545]


Federal

* On November 1, 2017, the official debt of the United States government was $20.5 trillion ($20,453,288,033,639).[546] This amounted to:

  • $62,703 for every person living in the U.S.[547]
  • $162,561 for every household in the U.S.[548]
  • 36% more than the combined consumer debt of every household in the U.S.[549]

* For comprehensive facts about the national debt, visit Just Facts’ research on this issue.

Footnotes

[1] Book: Encyclopedia of Contemporary American Social Issues, Volume 1: Business and Economy. Edited by Michael Shally-Jensen. ABC-CLIO, 2011. Chapter: “Income Tax, Personal.” By David N. Hyman, Pages 170–178.

Pages 170–172:

What Is Income?

Income is a flow of purchasing power from earnings of labor, capital, land and other sources that a person receives over a period of one year. The most comprehensive definition of income views it as an annual acquisition of rights to command resources. Income can be used to consume goods and services during the year it is received, or it can be stored up for future use in subsequent years. Income stored up for future use is saving, which increases a person’s net worth (a measure of the value of assets less debts). The most comprehensive measure of income views it as the sum of annual consumption plus savings, where savings is any increase in net worth that can result from not spending earnings and other forms of income or from increases in the market value of such assets as stocks, bonds, or housing that a person might own. The annual increase in the value of a person’s existing assets are capital gains, which can either be realized (converted to cash) by selling an asset or unrealized (not turned into cash in the current year).

[2] Report: “American Housing Survey for the United States: 2015–Appendix A. Subject Definitions and Table Index.” U.S. Department of Housing and Urban Development and U.S. Census Bureau. Last revised April 17, 2017. <www.census.gov>

Appendix A–16:

“Money income” is the income received on a regular basis (exclusive of certain money receipts such as capital gains and lump-sum payments) before payments for personal income taxes, social security, union dues, Medicare deductions, etc. It includes income received from wages, salary, commissions, bonuses, and tips; self-employment income from own nonfarm or farm businesses, including proprietorships and partnerships; interest, dividends, net rental income, royalty income, or income from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security Income (SSI); any cash public assistance or welfare payments from the state or local welfare office; retirement, survivor, or disability benefits; and any other sources of income received regularly such as Veterans’ (VA) payments, unemployment and/or worker’s compensation, child support, and alimony.

[3] Book: OECD Framework for Statistics on the Distribution of Household Income, Consumption and Wealth. Organization for Economic Cooperation and Development, 2013. <www.keepeek.com>

Pages 27–28: “Income allows people to satisfy their needs and pursue many other goals that they deem important to their lives, while wealth makes it possible to sustain these choices over time.”

[4] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 2:

In 2013, according to the Congressional Budget Office’s estimates, average household market income—a comprehensive income measure that consists of labor income, business income, capital income (including capital gains), and retirement income—was approximately $86,000. Government transfers, which include benefits from programs such as Social Security, Medicare, and unemployment insurance, averaged approximately $14,000 per household. The sum of those two amounts, which equals before-tax income, was about $100,000, on average. In this report, CBO analyzed the distribution of four types of federal taxes: individual income taxes, payroll (or social insurance) taxes, corporate income taxes, and excise taxes. Taken together, those taxes amounted to about $20,000 per household, on average, in 2013.1 Thus, average after-tax income—which equals market income plus government transfers minus federal taxes—was about $80,000, and the average federal tax rate (federal taxes divided by before-tax income) was about 20 percent.

1 Data for 2013 are the most recent available with complete information about tax payments. For more details, see the appendix.

[5] Webpage: “Income.” U.S. Census Bureau. Accessed January 13, 2017 at <www.census.gov>

“The Census Bureau reports income from several major household surveys and programs. Each differs from the others in some way, such as the length and detail of its questionnaire, the number of households included (sample size), and the methodology used.”

[6] Webpage: “Subject Areas: Overview of BLS Statistics on Pay and Benefits.” U.S. Department of Labor, Bureau of Labor Statistics. Updated December 13, 2013. <www.bls.gov>

Overview of BLS Statistics on Pay and Benefits

BLS publishes a large amount of information on the wages, earnings, and benefits of workers. Generally, this information is categorized in one or more of the following ways:

• Geographic area (national, regional, state, metropolitan area, or county data)

• Occupation (such as teacher or carpenter)

• Industry (such as manufacturing or retail trade)

Additional categories such as age, sex, or union membership may be used in some cases.

[7] Webpage: “National Economic Accounts.” U.S. Department of Commerce, Bureau of Economic Analysis. Accessed January 16, 2017 at <www.bea.gov>

Personal Income and Outlays

• News Release: Personal Income and Outlays

includes highlights and associated tables

• Interactive Tables: National Income and Product Accounts Tables

• Charts and interactive tables:

• Comparison of Personal Saving in the NIPAs with Personal Saving in the Flow of Funds Accounts

• Comparison of the Personal Consumption Expenditures (PCE) Price Index with the Consumer Price Index (CPI)

• Information about the 2016 NIPA Annual Update

• Information on previous revisions of the NIPA accounts

• Selected Documentation:

• Information on the Consumer Spending estimates

[8] Webpage: “SOI Tax Stats—Individual Income Tax Return (Form 1040) Statistics.” Internal Revenue Service. Last reviewed or updated July 12, 2016. <www.irs.gov>

Featured Areas

• What’s new in the Individual area

• High Income Tax Returns

• Individual Form W-2

• Individual Income Tax Rates and Tax Shares

• Individual Income Tax Returns (Annual SOI Bulletin article & tables)

• Sales of Capital Assets

• Sole Proprietorships

• Special Studies on Individual Tax Return Data

• Taxpayers with the Top 400 Adjusted Gross Income

[9] Webpage: “Survey of Consumer Finances: About.” Board of Governors of the Federal Reserve System. Updated September 2, 2014. <www.federalreserve.gov>

The Survey of Consumer Finances (SCF) is normally a triennial cross-sectional survey of U.S. families. The survey data include information on families’ balance sheets, pensions, income, and demographic characteristics. Information is also included from related surveys of pension providers and the earlier such surveys conducted by the Federal Reserve Board. No other study for the country collects comparable information. Data from the SCF are widely used, from analysis at the Federal Reserve and other branches of government to scholarly work at the major economic research centers.

The survey has contained a panel element over two periods. Respondents to the 1983 survey were re-interviewed in 1986 and 1989. Respondents to the 2007 survey were re-interviewed in 2009.

The study is sponsored by the Federal Reserve Board in cooperation with the Department of the Treasury. Since 1992, data have been collected by the NORC at the University of Chicago.

To ensure the representativeness of the study, respondents are selected randomly using procedures described in the technical working papers on this web site. A strong attempt is made to select families from all economic strata.

Participation in the study is strictly voluntary. However, because only about 6,500 families were interviewed in the most recent study, every family selected is very important to the results. To maintain the scientific validity of the study, interviewers are not allowed to substitute respondents for families that do not participate. Thus, if a family declines to participate, it means that families like theirs may not be represented clearly in national discussions.

The confidentiality of the information provided in the study is of the highest importance to NORC and the Federal Reserve. Strenuous efforts are made to protect the privacy of participants, and in the history of the survey, there has never been a leak. The names of the participants in the survey are known only to NORC, which has more than 50 years of successful experience in collecting confidential information.

For the 1983 and 1989 surveys, a separate Survey of Pension Providers (SPP) was conducted to obtain detailed technical information on the pensions of SCF participants; data and documentation for the SPP appear under a separate link.

A link is also given for data and documentation from the 1962 Survey of Financial Characteristics of Consumers (SFCC) and the 1963 Survey of Changes in Family Finances (SCFF); these surveys are the most direct precursors of the SCF.

[10] Webpage: “Income: About.” U.S. Census Bureau. Accessed January 13, 2017 at <www.census.gov>

Census money income is defined as income received on a regular basis (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, Medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive part of their income in the form of noncash benefits, such as food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents which may take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc.

Data users should consider these elements when comparing income levels. Moreover, users should be aware that for many different reasons there is a tendency in household surveys for respondents to underreport their income. Based on an analysis of independently derived income estimates, the Census Bureau determined that respondents report income earned from wages or salaries much better than other sources of income and that the reported wage and salary income is nearly equal to independent estimates of aggregate income.

The Census Bureau also derives alternative income measures that systematically remove or add various income components such as deducting payroll taxes and federal and state income taxes and including the value of specific noncash benefits, food stamps, school lunches, housing subsidies, health insurance programs, and return on home equity. These alternative measures are derived from information collected in Census surveys along with information from other agencies such as the Centers for Medicare and Medicaid Services (CMS), the U.S. Bureau of Labor Statistics, the U.S. Department of Agriculture, the U.S. Internal Revenue Service, and the U.S. Office of Personnel Management (OPM).

Several major household surveys and programs conducted by the Census Bureau collect income data.

For highlights and links to each survey or program’s site, see the Surveys & Programs section of this subtopic site.

For more background on each survey or program, the differences between them, and how to choose the right data source, see the Guidance for Data Users section of this subtopic site.

[11] Working paper: “Alternative Measures of Household Income: BEA Personal Income, CPS Money Income, and Beyond.” By John Ruser, Adrienne Pilot, and Charles Nelson. U.S. Bureau of Economic Analysis, December 14, 2004. <www.bea.gov>

Pages 1–2:

Two of the most widely used measures of household income are BEA’s [Bureau of Economic Analysis’s] personal income and the Census Bureau’s money income. These two statistics spring from different traditions of measurement—personal income from national income accounting and money income from income distribution analysis. …

• The Current Population Survey (CPS) Annual Social and Economic Supplement is the source of the Census Bureau’s official national estimates of poverty. CPS money income is defined as total pre-tax cash income earned by persons, excluding certain lump sum payments and excluding capital gains.

• BEA estimates that personal income for the US was $8.678 trillion in 2001, as compared to a CPS money income estimate of $6.446 trillion. Over 64 percent of this $2.232 trillion gap—$1.429 trillion—can be accounted for by differences in the income types that are included in the two measures, including the $982 billion of property income that is counted in personal income but not in CPS money income.

• Half of the remaining $804 billion money income gap can be accounted for by BEA adjustments to proprietors’ income and wages and salaries for underreporting in BEA source data.

[12] Paper: “Alternative Measures of Household Income: BEA Personal Income, CPS Money Income, and Beyond.” By John Ruser, Adrienne Pilot, and Charles Nelson. U.S. Department of Commerce, Bureau of Economic Analysis, November 2004. <www.bea.gov>

Page 2:

The Census Bureau has developed a number of alternative measures of money

income that may measure economic well-being better than CPS money income.

These measures remove taxes, add in-kind transfers, add realized capital gains or

losses, and add the imputed return on equity in own home. The Census Bureau

has found that a broadened definition of income results in a more equal

distribution of income and tends to reduce the gaps between the incomes of

traditionally high- and low-income groups.

Page 4:

BEA personal income and Census money income

Two of the most widely used measures of household income are BEA’s personal income and the Census Bureau’s money income. These two measures differ in the scope of individuals covered, in the income items included, in the sources of the data and in the extent of disaggregation of the estimates. This section will discuss the general definitions, sources and uses of these two measures, while the next section presents a reconciliation of aggregate income estimates as a means of indicating the nature and size of differences.3

3A third widely used measure of income is IRS adjusted gross income (AGI). For a comparison of BEA personal income and IRS AGI, see Ledbetter (2004).

Pages 10–11:

Alternative Census Bureau Income Definitions

Description

The traditional money income concept is limited and does not provide a completely satisfactory measure of economic well-being. For example, money income (unlike BEA’s disposable income concept) does not include the effects of taxes and, therefore, does not reflect the effect of tax law changes on economic well-being. Similarly, the official measure of money income excludes the effect of noncash benefits (such as employment-related group health insurance and food stamps), which enhance economic well-being and are also included in BEA’s personal income. The Census Bureau has a fairly long history of producing estimates that address these shortcomings.

Since the early 1980s, the Census Bureau has published analysis showing the effect of using a broadened income definition on measures of economic well-being. Currently, annual Census Bureau reports on income and poverty show the effect of using an income measure that includes the effect of noncash benefits and taxes on the distribution of income, prevalence of poverty, and level of income inequality based on the 17 income definitions as summarized below:

Definition 1: official money income

Definition 1b: definition 1 plus capital gains/losses less taxes

Definition 2: definition 1 less government cash transfers

Definition 3: definition 2 plus capital gains/less capital losses

Definition 4: definition 3 plus the value of employment-related health benefits

Definition 5: definition 4 less Social Security payroll taxes

Definition 6: definition 5 less federal income taxes (excluding the Earned • Income Tax Credit)

Definition 7: definition 6 plus the Earned Income Tax Credit

Definition 8: definition 7 less state income taxes

Definition 9: definition 8 plus non-means-tested government cash transfers

Definition 10: definition 9 plus the value of Medicare

Definition 11: definition 10 plus the value of regular-price school lunches

Definition 12: definition 11 plus means-tested cash transfers

Definition 13: definition 12 plus the value of Medicaid

Definition 14a: definition 13 plus the value of other means-tested government noncash transfers less Medicare and Medicaid

Definition 14: definition 13 plus the value of other means-tested government noncash transfers

Definition 15: definition 14 plus net imputed return on equity in own home

Obviously, the construction of 17 definitions of income was not based on the premise that each of these definitions represented a viable income concept. Rather, the construction of so many income definitions was to facilitate the analysis that examines which components of a broadened income measure are most responsible for the significant changes in income summary measures as one transitions from the money income concept to an expanded definition of well-being. That said, there are several expanded income definitions that the Census Bureau has found useful to track trends and differences between groups. For example, the 2002 CPS income report (U.S. Bureau of the Census, 2003) highlighted four definitions of income in addition to the traditional money income definition. These were definitions 1b, 14a, 14, and 15. It should be noted that in the 2002 income report for the first time these alternative income measures were featured in the main body of the report and presented along with the money income measures (in previous reports these figures were examined in supplemental report sections).

[13] Webpage: “Comparability of Current Population Survey Income Data with Other Data.” U.S. Census Bureau. Accessed January 13, 2017 at <www.census.gov>

The concepts used in the SIPP and the March supplement to the Current Population Survey (CPS) differ in some regards. These differences occur primarily between components of the income definition used in each survey and the manner in which certain reference units are categorized. An explanation of these differences follows.

Two basic units of reference common to both the SIPP and CPS are people and households. Groups of people living together, when combined based on relationship, form family units. A family refers to a group of two or more people related by birth, marriage, or adoption who reside together (one of whom is the householder). Two or more people who live together and are related to one another, but not related to the householder, form an unrelated subfamily. People in unrelated subfamilies are not included in the count of family members in the CPS, but are included as family members for the SIPP.

A unique feature of a longitudinal survey, such as SIPP, is its ability to capture change over time. A cross-sectional survey, such as CPS, does not have this feature and can only provide a series of snapshots of the socio-economic conditions that exist at different fixed points in time. CPS data are based on the demographic characteristics as they existed at the time the survey was conducted and are applied to the economic characteristics that existed for the previous calendar year. The demographic data in the SIPP are collected with the economic data throughout the calendar year and are likely to have changed during the year. In order to incorporate the effect of changes over time in family compositions in measures of SIPP income data, the data are presented for people rather than families. People are characterized by the income of their respective family unit based on living arrangements each month during the calendar year.

The definition of income used in the SIPP is basically the same as in the CPS. It reflects money income before taxes and does not include the value of noncash benefits such as employer-provided health insurance, food stamps, or Medicaid. Differences do exist however, they are:

• Accrued interest on Individual Retirement Accounts (IRA’s) KEOGH retirement plans, 401(k), and U.S. savings bonds; and educational assistance are excluded in SIPP and counted in the CPS.

• Lump-sum or one-time payments such as inheritances, insurance settlements, and lump-sum payments from a pension or retirement plan are counted in the SIPP and excluded in the CPS.

• Self-employment income (both farm and nonfarm) is counted in the CPS as a net amount, gross receipts minus operating expenses. In the SIPP, self-employment income includes a regular salary and/or any other income from the business.

[14] Article: “Comparison of BEA Estimates of Personal Income and IRS Estimates of Adjusted Gross Income.” By Mark Ledbetter. Survey of Current Business, U.S. Department of Commerce, Bureau of Economic Analysis, November 2007. <www.bea.gov>

Page 35:

The Bureau of Economic Analysis (BEA) annually publishes a comparison of BEA’s measure of personal income and the Internal Revenue Service (IRS) measure of adjusted gross income (AGI); both are widely used measures of household income. This comparison features the “AGI gap,” which is the difference between BEA-derived estimates of adjusted gross income and the IRS estimate of adjusted gross income.

Key Terms

Adjusted gross income (AGI), for Federal income tax purposes, includes all income that is received in the form of money, property, and services that is not explicitly exempt by law.

Personal income is the income received by individuals, nonprofit institutions serving households, private noninsured welfare funds, and private trust funds from all sources. It includes income that is taxed, that is partly taxed (such as social security benefit payments), and that is tax-exempt (such as tax-exempt interest, nontaxable The AGI gap for each type of income is the difference transfer payments, and Medicare, Medicaid, and welfare benefit payments). It is the sum of “compensation of employees (received),” proprietors’ income, rental income, personal income receipts on assets, and personal current transfer receipts; contributions for government social insurance is subtracted. Personal income includes imputed income, but it excludes net gains from the sale of assets (capital gains), pension benefit payments, and employee and self-employed contributions for government social insurance. …

BEA-derived adjusted gross income is BEA’s conceptual measure of adjusted gross income without taxpayer misreporting. It is based on IRS tabulations of data from individual income tax returns, corporate income tax returns, nonfarm sole proprietorship income tax returns, partnership income tax returns, and extrapolated estimates for tax-exempt income and for private foundation income.

The AGI gap is the difference between the BEA-derived adjusted gross income and IRS adjusted gross income. The AGI gap for each type of income is the difference between the BEA-derived adjusted gross income for that type of income and the reallocated IRS adjusted gross income.

The relative AGI gap for each type of income shows the AGI gap by type of income as a percentage of the BEA-derived adjusted gross income by type of income.

Misreporting adjustments are adjustments to IRS source data that are designed to correct for the effects of taxpayer misreporting in the tax return tabulations and economic census data used in the NIPAs. These adjustments account for income that is underreported on tax returns and for the income that is earned by individuals who do not file tax returns.

[15] Webpage: “Frequently Asked Questions Related to the Poverty Guidelines and Poverty.” U.S. Department of Health & Human Services, Office of the Assistant Secretary for Planning and Evaluation. Updated September 3, 2015. <aspe.hhs.gov>

Are the Poverty Guidelines Before-Tax or After-Tax? Are They Gross Income or Net Income? What Definition of Income Is Used with the Poverty Guidelines?

There is no simple answer to these questions. When determining program eligibility, some agencies compare before-tax income to the poverty guidelines, while other agencies compare after-tax income. Likewise, eligibility can be dependent on gross income, net income, or some other measure of income. Federal, state, and local program offices that use the poverty guidelines for eligibility purposes may define income in different ways. To find out the specific definition of income (before-tax, after-tax, etc.) used by a particular program or activity, one must consult the office or organization that administers that program.

While there is no standard definition of income for program eligibility purposes, the Census Bureau uses a standard definition of income for computing poverty statistics based on the official poverty thresholds. More information is available on the Census Bureau’s web site.

[16] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 2:

In 2013, according to the Congressional Budget Office’s estimates, average household market income—a comprehensive income measure that consists of labor income, business income, capital income (including capital gains), and retirement income—was approximately $86,000. Government transfers, which include benefits from programs such as Social Security, Medicare, and unemployment insurance, averaged approximately $14,000 per household. The sum of those two amounts, which equals before-tax income, was about $100,000, on average. In this report, CBO analyzed the distribution of four types of federal taxes: individual income taxes, payroll (or social insurance) taxes, corporate income taxes, and excise taxes. Taken together, those taxes amounted to about $20,000 per household, on average, in 2013.1 Thus, average after-tax income—which equals market income plus government transfers minus federal taxes—was about $80,000, and the average federal tax rate (federal taxes divided by before-tax income) was about 20 percent.

1 Data for 2013 are the most recent available with complete information about tax payments. For more details, see the appendix.

Pages 1–2:

Market income consists of labor income, business income, capital gains (profits realized from the sale of assets), capital income excluding capital gains, income received in retirement for past services, and other sources of income.

Government transfers are cash payments and in-kind benefits from social insurance and other government assistance programs. Those transfers include payments and benefits from federal, state, and local governments.

Before-tax income is market income plus government transfers. …

Income groups are created by ranking households by their size-adjusted income. A household consists of people sharing a housing unit, regardless of their relationships. Each income quintile (fifth) contains approximately equal numbers of people but different numbers of households. Similarly, each percentile (hundredth) contains approximately equal numbers of people but different numbers of households. If a household has negative income (that is, if its business or investment losses are larger than its other income), it is excluded from the lowest income group but included in totals.

Household income over time is adjusted for inflation using the price index for personal consumption expenditures as calculated by the Bureau of Economic Analysis.

[17] Webpage: “Income: About.” U.S. Census Bureau, Accessed January 13, 2017 at <www.census.gov>

Census money income is defined as income received on a regular basis (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, Medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive part of their income in the form of noncash benefits, such as food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents which may take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc.

[18] Paper: “Alternative Measures of Household Income: BEA Personal Income, CPS Money Income, and Beyond.” By John Ruser, Adrienne Pilot, and Charles Nelson. U.S. Department of Commerce, Bureau of Economic Analysis, November 2004. <www.bea.gov>

Page 1:

Two of the most widely used measures of household income are BEA’s personal income and the Census Bureau’s money income. These two statistics spring from different traditions of measurement—personal income from national income accounting and money income from income distribution analysis. Yet, many of the conceptual difficulties in developing guidelines for income distribution statistics are the same or similar to the problems encountered in specifying guidelines for national income accounting.

[19] Report: “Source and Accuracy of Estimates for Income and Poverty in the United States: 2014 and Health Insurance Coverage in the United States: 2014.” U.S. Census Bureau, July 2015. <www2.census.gov>

Page 1:

The estimates in the reports Income and Poverty in the United States: 2014 and Health Insurance Coverage in the United States: 2014 come from the 2015 Annual Social and Economic Supplement (ASEC) of the Current Population Survey (CPS).1 The Census Bureau conducts the CPS ASEC over a 3-month period, in February, March, and April, with most data collection occurring in the month of March. The CPS ASEC uses two sets of questions, the basic CPS and a set of supplemental questions. The CPS, sponsored jointly by the Census Bureau and the U.S. Bureau of Labor Statistics, is the country’s primary source of labor force statistics for the entire population. The Census Bureau and the U.S. Bureau of Labor Statistics also jointly sponsor the CPS ASEC.

1 Portions of the health insurance data in the report are based on the American Community Survey (ACS). Please refer to the ACS Source and Accuracy Statement: www2.census.gov/programs-surveys/acs/tech-docs/accuracy/ACS_Accuracy_of_Data_2014.pdf

[20] Paper: “Income Measurement Error in Surveys: A Review.” By Jeffrey C. Moore, Linda L. Stinson, and Edward J. Welniak. U.S. Census Bureau, December 1997. <www.census.gov>

Page 2:

In its role as producer of the nation’s “official statistics,” the Census Bureau has, over the years, examined the quality of its income estimates through comparisons to independent estimates derived from independent, outside sources—e.g., the National Income and Products Accounts (NIPA), individual income tax data, Social Security Administration records, caseload statistics from agencies that administer various transfer programs, etc. Table 1, derived from Coder and Scoon-Rogers (1995), summarizes the results of recent work comparing survey-based estimates and independent benchmarks for an extensive set of income types. The Census Bureau’s two major income surveys, the Survey of Income and Program Participation (SIPP) and the Current Population Survey’s (CPS) March Income Supplement, supply the survey estimates. Two conclusions are immediately obvious from Table 1. First, a primary goal of SIPP was to provide more complete income data than CPS. The fact that SIPP’s estimates are generally closer to the benchmarks than CPS’s suggests that SIPP has had some success in meeting that goal—especially, perhaps, for transfer program income. Second, however, and even more pronounced, is the consistency with which the survey estimates fall short of the benchmarks—across surveys, across time, and across income categories.

[21] Webpage: “SOI Tax Stats – Individual Statistical Tables by Tax Rate and Income Percentile.” Internal Revenue Service. Updated August 31, 2016. <www.irs.gov>

“On this page you will find a complete list of tables from various sources and publications classified by tax rate and income percentile.”

[22] Working Paper: “Household Incomes in Tax Data: Using Addresses to Move from Tax Unit to Household Income Distributions.” By Jeff Larrimore, Jacob Mortenson, and David Splinter. Board of Governors of the Federal Reserve System, January 3, 2017. <doi.org>

Page 2:

Over the past decade, research based on administrative IRS tax return data has greatly expanded our understanding of incomes at the top of the U.S. income distribution (see e.g. Piketty and Saez (2003) and Atkinson, Piketty and Saez (2011) for a review of the literature using tax record data). Despite these advances in observing top incomes, researchers using tax data have been forced to adapt their analysis to fit the limitations of IRS tax return data. In particular, an inability to observe information on non-filers in the tax return data have largely restricted analyses using tax records to the upper end of the income distribution. Additionally, the inability to observe households, which may contain several tax units or non-filers, have precluded analyses at the household level—which are standard in both national and cross-national distributional studies.

Pages 2–3:

The inability of tax records to capture certain information on non-filers is a well-known limitation of the tax data. The standard administrative tax data excludes the nearly 15 percent of adults and 13 percent of household heads who do not file a tax return and are not claimed as dependents each year (Auten and Gee, 2009; Molloy, Smith, and Wozniak, 2011). These non-filers are not missing at random, and are instead primarily concentrated in the lower-tail of the distribution—which means that researchers using tax return data observe only a truncated version of the income distribution. Most researchers partially overcome this problem by using tax return data only to analyze the top of the distribution and assuming that all non-filers have an income equal to 20 or 30 percent of average filer income (Piketty and Saez, 2003; Auten and Splinter, 2016). However, such an approach cannot be expanded to analyze lower-tail or broad-based inequality measures because it does not capture observation-level incomes for these non-filers.

[23] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 2: “Household income over time is adjusted for inflation using the price index for personal consumption expenditures as calculated by the Bureau of Economic Analysis.”

[24] Webpage: “Poverty: How the Census Bureau Measures Poverty.” U.S. Census Bureau. Accessed January 19, 2017 at <www.census.gov>

Following the Office of Management and Budget’s (OMB) Statistical Policy Directive 14, the Census Bureau uses a set of money income thresholds that vary by family size and composition to determine who is in poverty. If a family’s total income is less than the family’s threshold, then that family and every individual in it is considered in poverty. The official poverty thresholds do not vary geographically, but they are updated for inflation using the Consumer Price Index (CPI-U). The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps).

[25] Statement: “BLS Statement on the Use of the CPI-U-RS.” Consumer Price Index, Bureau of Labor Statistics, March 2011. <www.bls.gov>

Updated CPI-U-RS, All Items and All items less food and energy, 1978–2010

BLS Statement on the Use of the CPI-U-RS

The Bureau of Labor Statistics (BLS) has made numerous improvements to the Consumer Price Index (CPI) over the past thirty-plus years. While these improvements make the present and future CPI more accurate, historical price index series are not adjusted to reflect the improvements. Many researchers, however, expressed an interest in having a historical series that was measured consistently over the entire period. Accordingly, the Consumer Price Index research series using current methods (CPI-U-RS) presents an estimate of the CPI for all Urban Consumers (CPI-U) from 1978 to present that incorporates most of the improvements made over that time span into the entire series.

The CPI-U-RS is in some ways an extension of the CPI-U-X1, an experimental series that shows what the inflation rate in the CPI-U might have been, if the current rental equivalence method of measuring the cost of homeownership had been in place prior to 1983.

The CPI-U-RS has some limitations. First, most estimates are based on BLS research covering a short period of time and extrapolated to a longer period. Therefore, there is considerable uncertainty surrounding the magnitude of the adjustments. Second, there have been several improvements in the CPI not incorporated into the CPI-U-RS, either because they do not represent changes in methodology, because they had negligible impacts on the CPI’s growth rate, or because it was impossible to systematically estimate the impacts of the new methods in past years.

Nonetheless, the CPI-U-RS can serve as a valuable proxy for researchers needing a historical estimate of inflation using current methods. The direct adjustment of individual CPI index series makes this the most detailed and systematic estimate available of a consistent CPI series.

[26] Working Paper: “A Comparison of Income Concepts: IRS Statistics of Income, Census Current Population Survey, and BLS Consumer Expenditure Survey.” By Eric L. Henry and Charles D. Day. Internal Revenue Service, 2005. <www.irs.gov>

Page 149:

Several Federal Government agencies produce statistics on individual and household income. Because of the differing purposes to which their data will be put, agencies use different definitions for income (income concepts), as well as different reporting units, sample designs, collection modes, and processing rules. Data users are faced with an array of choices, often without much help to sort out which data series best meets their needs or much guidance to reconcile results based on different sources of data.

[27] Report: “Income and Poverty in the United States: 2015 (Current Population Reports).” By Bernadette D. Proctor, Jessica L. Semega, and Melissa A. Kollar. U.S. Census Bureau, September 2016. <www.census.gov>

Page 3: “The income and poverty estimates shown in this report are based solely on money income before taxes and do not include the value of noncash benefits, such as those provided by the Supplemental Nutrition Assistance Program (SNAP), Medicare, Medicaid, public housing, or employer-provided fringe benefits.”

Page 21:

Data on income collected in the ASEC by the U.S. Census Bureau cover money income received (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, Medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive noncash benefits, such as Supplemental Nutrition Assistance/ food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents, which often take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc. Data users should consider these elements when comparing income levels.

[28] Book: Canberra Group Handbook on Household Income Statistics (2nd edition). United Nations Economic Commission for Europe, 2011. <www.unece.org>

Pages 2–3:

A household’s economic well-being can be expressed in terms of its access to goods and services. The more that a household can consume, the higher its level of economic wellbeing. …

Consumption is therefore an indicator of economic well-being. However, a household may be able to choose not to consume the maximum amount it could in any given period but to save at least some of the resources it has available. By saving, households can accumulate wealth through the purchase of assets which will generate income at a later date and serve as a ‘nest egg’ for spending at a later time when income levels may be lower, or needs higher. As well as possibly earning a return for the household, ownership of wealth also affects their broader economic power and is another aspect of economic well-being. For example, households that own their own home outright generally have lower housing costs and may therefore have lower income requirements to satisfy their desired standard of living.

Thus to capture fully the extent of a household’s economic well-being it is desirable to look at a number of different aspects of their economic situation, including not only their income, but also their levels of wealth, changes in the value of that wealth and levels of consumption.

[29] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 2: “Income groups are created by ranking households by their size-adjusted income. A household consists of people sharing a housing unit, regardless of their relationships.”

[30] Working paper: “Examining the Middle Class in the United States Using the Lens of the Supplemental Poverty Measure.” By Trudi Renwick and Kathleen Short. U.S. Census Bureau, September 30, 2014. <www.census.gov>

Pages 1–2:

II. Approaches to Defining the Middle Class

While much has been written on the middle class, there is no widely accepted approach to defining the middle class. Some analyses of the middle class equate being in the middle class with having income in the middle of the income distribution. Other analyses include in the middle class anyone who self-identifies as middle class. A third approach is to count as middle class anyone who has achieved certain aspirations – owning their own home, having savings for retirement and/or the ability to send their children to college. As may be expected, these disparate approaches do not identify the same people as being in the middle class.

Of the analyses that equate being in the middle class with having an income in the middle of the income distribution, many use median household income to “define” the middle class. This metric is a useful summary measure that can be tracked over time and across countries. Each year the Census Bureau publishes a number of tables providing estimates of median household income and median family income.

[31] Webpage: “Glossary.” U.S. Census Bureau. Accessed April 20, 2017 at <www.census.gov>

Median

This measure represents the middle value (if n is odd) or the average of the two middle values (if n is even) in an ordered list of data values. The median divides the total frequency distribution into two equal parts: one-half of the cases fall below the median and one-half of the cases exceed the median.

For example, the median income is the amount which divides the income distribution into two equal groups, one having incomes above the median, and the other having incomes below the median. The median for households, families, and unrelated individuals is based on all households, families, and unrelated individuals, respectively. The median for people is based on people with income.

[32] Report: “Was JFK Wrong? Does Rising Productivity No Longer Lead to Substantial Middle Class Gains?” By Stephen J. Rose. Information Technology & Innovation Foundation, December 16, 2014. <www2.itif.org>

Page 3:

So the phrase “stagnating income” does not apply to the experiences of real people but to “similarly-situated” people. This cumbersome phrase means that accurate comparisons involve comparing slots along the income ladder at different points in time. … There is always a group of families in the middle of the distribution; it is just not the same families. One should think of this comparison as the “group” comparison—i.e., comparing the median (or another wrung on the income ladder) over a specified number of years.

In other words, at any specific time, the economy is composed of people of varying ages and income. The people in the lowest rungs of the income ladder are often young people and older people with lots of assets, fewer expenses, and large government subsidies through Medicare, Social Security, and sometimes Medicaid. If we look 10, 20, or 30 years later, there has been a large changing of places (think of what happens on a crowded escalator with the same number of people at each level even though it is different people). Younger people are no longer on the bottom, but have moved up to a higher place on the income ladder; some old people have died and been replaced by people who were formerly in their prime-earning years; and new independent young people who were part of families now populate the lower rungs of the income ladder.

This means that comparing the income gains of the bottom three quintiles in 1979 and 2007 has little to do with the path of real families. Instead it is a commentary on the overall structure of the economy in that it compares low income people in 1979 to low income people in 2007 even though they aren’t the same people. … For example, the median income of those 20-31 in 1979 and married was $51,800 (2007 dollars), while 28 years later in 2007, the median of those 48 to 59 and married was $87,200.7

[33] Paper: “New Perspectives on Income Mobility and Inequality.” By Gerald Auten, Geoffrey Gee, and Nicholas Turner. National Tax Journal, December 2013. <www.law.upenn.edu>

Page 893:

This study examines several dimensions of income mobility and inequality—mobility of individuals through their peak earnings years, intergenerational mobility, and persistence in the top 1 percent. Its main findings can be summarized as follows. Half of those age 35–40 in the bottom quintile of their cohort moved to higher quintiles 20 years later; over 60 percent moved up relative to the full population. About 70 percent of dependents from low-income households were themselves in higher quintiles 20 years later. Younger generations gradually replaced those that dominated the top percentile in 1987. The results show the importance of life cycle effects and the changing composition of top income groups.

[34] Webpage: “Glossary of Statistical Terms: Purchasing Power Parities (PPPs).” Organization for Economic Co-operation and Development. Last updated June 11, 2013. <stats.oecd.org>

Definition:

Purchasing power parities (PPPs) are the rates of currency conversion that equalise the purchasing power of different currencies by eliminating the differences in price levels between countries. In their simplest form, PPPs are simply price relatives which show the ratio of the prices in national currencies of the same good or service in different countries.

Context:

PPPs are calculated in three stages:

– first for individual products,

– then for groups of products or basic headings and,

– finally, for groups of basic headings or aggregates.

The PPPs for basic headings are unweighted averages of the PPPs for individual products. The PPPs for aggregates are weighted averages of the PPPs for basic headings.

The weights used are the expenditures on the basic headings. PPPs at all stages are price relatives. They show how many units of currency A need to be spent in country A to obtain the same volume of a product or a basic heading or an aggregate that X units of currency B purchases in country B.

In the case of a single product, the “same volume” means “identical volume”. But in the case of the complex assortment of goods and services that make up an aggregate such as GDP, the “same volume” does not mean an “identical basket of goods and services”.

The composition of the basket will vary between countries according to their economic, social and cultural differences, but each basket will provide equivalent satisfaction or utility.

Also referred to as “parity” or “parities”.

[35] Report: “International Comparisons of GDP Per Capita and Per Hour, 1960–2011.” U.S. Bureau of Labor Statistics, November 7, 2012. <www.bls.gov>

Page 1: “GDP per capita, when converted to U.S. dollars using purchasing power parities, is the most widely used income measure for international comparisons of living standards.”

Page 2:

Gross Domestic Product (GDP) is defined as the value of all market and some nonmarket goods and services produced within a country’s geographic borders. As such, it is the most comprehensive measure of a country’s economic output that is estimated by statistical agencies. GDP per capita may therefore be viewed as a rough indicator of a nation’s economic well-being, while GDP per hour worked can provide a general picture of a country’s productivity.

[36] Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “3. Household Income”

NOTE: The next footnote provides relevant context about this data.

[37] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTES: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[38] Calculated with the dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “3. Household Income”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[39] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[40] Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “5. Median Household Income, 1979 to 2013 … Before-Tax Income … 2013 [=] 79,200 … After-tax Income [=] 69,200 … A median is the midpoint of a distribution. Like other percentile calculations in this report, medians are calculated by ranking people by their household income. Median household income, therefore, is the household income of the person at the midpoint of the income distribution.

NOTE: The next footnote provides relevant context about this data.

[41] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 6:

For this analysis, federal taxes include individual income taxes, payroll taxes, corporate income taxes, and excise taxes, which together accounted for 93 percent of all federal revenues in fiscal year 2013. Revenues from states’ deposits for unemployment insurance, estate and gift taxes, miscellaneous fees and fines, and net income earned by the Federal Reserve, which make up the remaining 7 percent, are not allocated to households in this analysis, mainly because it is uncertain how to attribute those revenues to particular households.

Page 11: “Because of the complexity of estimating state and local taxes for individual households, this report considers federal taxes only. Researchers differ about whether state and local taxes are, on net, regressive, proportional, or slightly progressive, but most agree that state and local taxes are less progressive than federal taxes.”

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[42] Calculated with the dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “5. Median Household Income, 1979 to 2013 … 2013 Dollars … Year [=] 1979 … Before-Tax Income … Unadjusted [=] 61,400 … After-Tax Income … Unadjusted [=] 49,500 … Year [=] 2013 … Before-Tax Income … Unadjusted [=] $79,200 … After-Tax Income … Unadjusted [=] $69,200”

CALCULATIONS:

  • $79,200 income in 2013 – $61,400 income in 1979 = $17,800
  • $17,800 / $61,400 income in 1979 = 29%
  • $69,200 after-tax income in 2013 – $49,500 after-tax income in 1979 = $19,700
  • $19,700 / $49,500 after-tax income in 1979 = 40%

NOTE: The next footnote provides relevant context about this data.

[43] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 6:

For this analysis, federal taxes include individual income taxes, payroll taxes, corporate income taxes, and excise taxes, which together accounted for 93 percent of all federal revenues in fiscal year 2013. Revenues from states’ deposits for unemployment insurance, estate and gift taxes, miscellaneous fees and fines, and net income earned by the Federal Reserve, which make up the remaining 7 percent, are not allocated to households in this analysis, mainly because it is uncertain how to attribute those revenues to particular households.

Page 11: “Because of the complexity of estimating state and local taxes for individual households, this report considers federal taxes only. Researchers differ about whether state and local taxes are, on net, regressive, proportional, or slightly progressive, but most agree that state and local taxes are less progressive than federal taxes.”

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[44] Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “5. Median Household Income, 1979 to 2013”

NOTES:

  • An Excel file containing the data is available upon request.
  • The next footnote provides relevant context about this data.

[45] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 6:

For this analysis, federal taxes include individual income taxes, payroll taxes, corporate income taxes, and excise taxes, which together accounted for 93 percent of all federal revenues in fiscal year 2013. Revenues from states’ deposits for unemployment insurance, estate and gift taxes, miscellaneous fees and fines, and net income earned by the Federal Reserve, which make up the remaining 7 percent, are not allocated to households in this analysis, mainly because it is uncertain how to attribute those revenues to particular households.

Page 11: “Because of the complexity of estimating state and local taxes for individual households, this report considers federal taxes only. Researchers differ about whether state and local taxes are, on net, regressive, proportional, or slightly progressive, but most agree that state and local taxes are less progressive than federal taxes.”

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[46] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[47] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income). …

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

[48] Calculated with the dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “6. Sources of Income for All Households by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[49] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[50] Calculated with the dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “6. Sources of Income for All Households by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[51] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[52] Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “6. Sources of Income for All Households by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[53] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 6:

For this analysis, federal taxes include individual income taxes, payroll taxes, corporate income taxes, and excise taxes, which together accounted for 93 percent of all federal revenues in fiscal year 2013. Revenues from states’ deposits for unemployment insurance, estate and gift taxes, miscellaneous fees and fines, and net income earned by the Federal Reserve, which make up the remaining 7 percent, are not allocated to households in this analysis, mainly because it is uncertain how to attribute those revenues to particular households.

Page 11: “Because of the complexity of estimating state and local taxes for individual households, this report considers federal taxes only. Researchers differ about whether state and local taxes are, on net, regressive, proportional, or slightly progressive, but most agree that state and local taxes are less progressive than federal taxes.”

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income). …

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program

[54] Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “6. Sources of Income for All Households by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[55] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 6:

For this analysis, federal taxes include individual income taxes, payroll taxes, corporate income taxes, and excise taxes, which together accounted for 93 percent of all federal revenues in fiscal year 2013. Revenues from states’ deposits for unemployment insurance, estate and gift taxes, miscellaneous fees and fines, and net income earned by the Federal Reserve, which make up the remaining 7 percent, are not allocated to households in this analysis, mainly because it is uncertain how to attribute those revenues to particular households.

Page 11: “Because of the complexity of estimating state and local taxes for individual households, this report considers federal taxes only. Researchers differ about whether state and local taxes are, on net, regressive, proportional, or slightly progressive, but most agree that state and local taxes are less progressive than federal taxes.”

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income). …

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program

[56] Article: “Unemployment.” By Lawrence H. Summers.† The Concise Encyclopedia of Economics (2nd edition). Edited by David Henderson. Liberty Fund, 2008. <www.econlib.org>

The second way government assistance programs contribute to long-term unemployment is by providing an incentive, and the means, not to work. Each unemployed person has a “reservation wage”—the minimum wage he or she insists on getting before accepting a job. Unemployment insurance and other social assistance programs increase that reservation wage, causing an unemployed person to remain unemployed longer.

NOTE: † “Former Treasury Secretary Lawrence H. Summers is one of America’s leading economists. In addition to serving as 71st Secretary of the Treasury in the Clinton Administration, Dr. Summers served as Director of the White House National Economic Council in the Obama Administration, as President of Harvard University, and as the Chief Economist of the World Bank.” [Webpage: “Biography.” Larry Summers. Accessed December 11, 2017 at <larrysummers.com>]

[57] Paper: “Unemployment Durations and Extended Unemployment Benefits in Local Labor Markets.” By Stepan Jurajda and Frederick J. Tannery. Industrial and Labor Relations Review, January 2003. Pages 324–348. <home.cerge-ei.cz>

Page 324:

Many empirical studies have confirmed the theoretical prediction that longer-term Unemployment Insurance (UI) entitlement leads to longer unemployment duration. Most of those studies have examined special programs that provide extra weeks of unemployment benefits when unemployment rates in the region are higher. Hence, they must distinguish if the longer unemployment duration among UI claimants observed in these cases is due to the extended benefits or to the adverse labor market conditions that trigger those extensions. In contrast, this paper measures the effect of identical entitlement extensions across two labor markets facing very different demand conditions—Pittsburgh and Philadelphia, over the years 1980–85. The results confirm findings of the existing literature and indicate that the adverse effect of longer entitlement changes relatively little in response to variation in demand conditions.

Page 343: “Over 28% of claimants even in the depressed Pittsburgh labor market were able to find work as soon as benefits ended, and two-thirds of this group found new jobs.”

Page 345: “First, the high incidence of exhausted benefits in both extended benefits programs, combined with the dramatic spike at the moment of exhaustion even in deeply depressed labor markets, suggests that greater focus needs to be put on incentives for rapid reemployment.”

[58] Report: “The 2012 Long-Term Budget Outlook.” By Joyce Manchester and others. Congressional Budget Office, June 2012. <cbo.gov>

Pages 36–37:

Similarly, a lower marginal tax rate on labor income increases the incentive to work, raising the number of hours people work and therefore the amount of output and income. However, because that lower marginal tax rate increases people’s after-tax income from the work they are already doing, they do not need to work as much to maintain their standard of living, which reduces the supply of labor. Again, CBO concludes, as do most analysts, that the former effect outweighs the latter and that lower marginal tax rates on labor income increase the labor supply. A higher marginal tax rate on labor income has the opposite effect.

To reflect the high degree of uncertainty that attends the effect of the marginal tax rate on labor supply, CBO produced estimates of the economic effects of the two budget scenarios using three assumptions about how people would adjust the number of hours they worked in response to changes in marginal tax rates (and changes in pretax wages as well):

• A “strong labor supply response,” under which workers’ response is on the high side of the consensus range of empirical estimates;

• A “weak labor supply response,” under which workers’ response is on the low side of the consensus range; and

• A “medium labor supply response,” under which workers’ response is roughly midway between strong and weak.

The responsiveness of labor supply to taxes is often expressed as the total wage elasticity (the change in total labor income caused by a 1 percent change in after-tax wages). The total wage elasticity, in turn, has two components: a substitution elasticity (which measures the effect of changes in marginal tax rates) and an income elasticity (which measures the effect of changes in average tax rates). In this analysis, CBO’s assumptions for labor supply response correspond to total wage elasticities of about 0.35 for the strong response (composed of a substitution elasticity of 0.35 and an income elasticity of zero); about -0.05 for the weak response (composed of a substitution elasticity of 0.15 and an income elasticity of -0.20); and about 0.15 for the medium response (composed of a substitution elasticity of 0.25 and an income elasticity of -0.1). (Reflecting CBO’s review of research in this area, the strong labor supply response is substantially stronger, and the weak labor supply response slightly weaker, than those used for CBO’s 2011 long-term budget outlook.)

[59] Report: “Federal Tax Treatment of Individuals.” U.S. Congress, Joint Committee on Taxation September 12, 2011. <www.jct.gov>

Pages 25–26:

Some analysts have suggested that high marginal tax rates may alter taxpayers’ decisions to work and alter economic output. For example, assume a taxpayer in the 35 percent tax bracket is considering working on an overtime assignment which pays $1,000, and which the taxpayer would certainly choose to undertake if he or she received the full $1,000. However, the taxpayer’s net of tax remuneration for the project is $650. The taxpayer may feel the net remuneration of $650 is insufficient to offset the loss of leisure time and the effort that would be expended to complete the project. If the taxpayer chooses not to work, society loses the benefit of his or her labor.

There is disagreement among economists on the extent to which labor supply decisions are affected by the marginal tax rate on labor income. Empirical evidence indicates that taxpayer response is likely to vary depending upon a number of taxpayer-specific factors. In general, findings indicate that the labor supply of so called “primary earners” tends to be less responsive to changes in marginal tax rates than is the labor supply of “secondary earners.”26 Some have suggested that the labor supply decision of the lower earner or “secondary earner” in married households may be quite sensitive to the household’s effective marginal tax rate.27 Other evidence suggests the decision to work additional hours may be less sensitive to changes in the marginal tax rate than the decision to enter the labor force.28 That is, there may be more effect on an individual currently not in the labor force than on an individual already in the labor force.

26 The phrase “primary earner” refers to the individual in the household who is responsible for providing the largest portion of household income. “Secondary earners” are earners other than the primary earner.

27 For a review of econometric studies on labor supply of so-called primary and secondary earners, see United States Congress, Congressional Budget Office Memorandum, “Labor Supply and Taxes,” 2006, and Charles L. Ballard, John B. Shoven, and John Whalley, “General Equilibrium Computations of the Marginal Welfare Costs of Taxes in the United States,” American Economic Review, 75, March 1985. See also John Pencavel, “A Cohort Analysis of the Association between Work Hours and Wages Among Men,” Journal of Human Resources 37(2), 2002, pp. 251–274; and Francine D. Blau and Lawrence M. Kahn “Changes in the Labor Supply Behavior of Married Women: 1980–2000,” Journal of Labor Economics, July 2007.

[60] Article: “Employer Costs for Employee Compensation: Tracking Changes in Benefit Costs.” By William J. Wiatrowski. U.S. Bureau of Labor Statistics Compensation and Working Conditions, Spring 1999. <www.bls.gov>

Page 32:

In the final four decades of the 20th century, employee compensation, as measured by employer costs, has undergone dramatic shifts. In 1959, cash payments (including straight-time pay, premium pay, bonuses, and paid leave) comprised 91 percent of all compensation costs for production workers in manufacturing industries; this fell to 78 percent by 1998. The remaining employer compensation costs were for benefits—those non-wage items that generally provide time off, insurance protection, and retirement security. In 1959, the largest proportion of benefit expenditures was for paid time off; by 1998, the largest benefit expenditure was for legally required items, such as Social Security and Medicare.

NOTE: For more facts about how government programs sometimes divert employee compensation away from wages, see the section of this research on employee compensation.

[61] Report: “Estimated Macroeconomic Impacts of the American Recovery and Reinvestment Act of 2009.” Congressional Budget Office, March 2, 2009. <www.cbo.gov>

Page 2:

In contrast to its positive near-term macroeconomic effects, the legislation will reduce output slightly in the long run, CBO estimates. The principal channel for that effect, which would also arise from other proposals to provide short-term economic stimulus by increasing government spending or reducing revenues, is that the law will result in an increase in government debt. To the extent that people hold their wealth as government bonds rather than in a form that can be used to finance private investment, the increased debt will tend to reduce the stock of productive private capital. In economic parlance, the debt will “crowd out” private investment.

[62] Report: “The Budget and Economic Outlook: Fiscal Years 2013 to 2023.” U.S. Congressional Budget Office, February 2013. <www.cbo.gov>

Page 8: “Because federal borrowing generally reduces national saving, the stock of capital assets, such as equipment and structures, will be smaller and aggregate wages will be less than if the debt were lower.”

[63] Calculated with the dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “6. Sources of Income for All Households by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[64] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[65] Calculated with the dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “6. Source of Income for All Households by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[66] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[67] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 9: “Social Security and Medicare are the two largest government transfer programs. Benefits from those programs are provided mostly to elderly households, many of which have low market income.”

[68] Report: “Major Decisions in the House and Senate on Social Security.” By Geoffrey Kollmann and Carmen Solomon-Fears. Domestic Social Policy Division, Social Security Administration, March 26, 2001. <www.ssa.gov>

[House Resolution] 7225, the Social Security Amendments of 1956, was signed by President Eisenhower on August 1, 1956. The amendments provided benefits, after a 6-month waiting period, for permanently and totally disabled workers aged 50 to 64 who were fully insured and had at least 5 years of coverage in the 10-year period before becoming disabled; to a dependent child 18 and older of a deceased or retired insured worker if the child became disabled before age 18; to women workers and wives at the age of 62, instead of 65, with actuarially reduced benefits; reduced from 65 to 62 the age at which benefits were payable to widows or parents, with no reduction; extended coverage to lawyers, dentists, veterinarians, optometrists, and all other self-employed professionals except doctors increased the tax rate by 0.25% on employer and employee each (0.375% for self-employed people) to finance disability benefits (thereby raising the aggregate tax rate ultimately to 4.25%); and created a separate disability insurance (DI) trust fund. The Social Security program now consisted of old-age, survivors, and disability insurance….

NOTE: For more facts about Social Security, visit Just Facts’ comprehensive research on this issue.

[69] Report: “Medicare Primer.” By Patricia A. Davis. Congressional Research Service, July 1, 2010. <aging.senate.gov>

Page 1: “Medicare is a federal insurance program that pays for covered health care services of qualified beneficiaries. It was established in 1965 under Title XVIII of the Social Security Act as a federal entitlement program to provide health insurance to individuals 65 and older, and has been expanded over the years to include permanently disabled individuals under 65.”

NOTE: For more facts about Medicare, visit Just Facts’ comprehensive research on this issue.

[70] Calculated with data from:

a) “2017 Annual Report of the Board of Trustees of The Federal Old-Age and Survivors Insurance and Disability Insurance Trust Funds.” United States Social Security Administration, July 13, 2017. <www.ssa.gov>

Pages 61–62: “Table IV.B3.—Covered Workers and Beneficiaries, Calendar Years 1945–2095 … 2016 beneficiariesb (in thousands) = 60,539 … b Beneficiaries with monthly benefits in current-payment status as of June 30.”

b) Dataset: “Monthly Population Estimates for the United States: April 1, 2010 to December 1, 2017 (NA-EST2016-01).”, U.S. Census Bureau, Population Division, December 2016. <www2.census.gov>

“Resident Population … July 1, 2016 [=] 323,127,513”

CALCULATION: 60,539,000 beneficiaries / 323,127,513 people = 19%

[71] Calculated with data from:

a) Report: “Medicare Primer.” By Patricia A. Davis and others. Congressional Research Service, August 2, 2017. <www.fas.org>

Page 2 (of PDF): “In FY2017, the program will cover approximately 58 million persons (49 million aged and 9 million disabled) at a total cost of about $708 billion.”

b) Dataset: “Monthly Estimates of the Resident Population for the United States, Regions, States, and Puerto Rico: April 1, 2010 to December 1, 2017.” U.S. Census Bureau, January 2017. <www2.census.gov>

“Resident Population… July 1, 2017 [=] 325,344,115”

CALCULATION: 58,000,000 Medicare enrollees / 325,344,115 population = 18%

[72] Report: “Dynamics of Economic Well-Being: Participation in Government Programs, 2009–2012: Who Gets Assistance?” By Shelley K. Irving and Tracy A. Loveless. U.S. Census Bureau, May 2015. <www.census.gov>

Page 1:

This report focuses on the participation and characteristics of people who received benefits from any of the following means-tested assistance programs:1

• Medicaid

• Supplemental Nutrition Assistance Program (SNAP)

• Housing Assistance

• Supplemental Security Income (SSI)

• Temporary Assistance for Needy Families (TANF)

• General Assistance (GA)

The data come from the 2008 Panel of the Survey of Income and Program Participation (SIPP) and cover calendar years 2009 through 2012.3 The SIPP is a longitudinal survey, which means that, unlike periodic point-in-time surveys, such as the Current Population Survey (CPS), the SIPP follows the same people over time.4

1 Means-tested programs are those that require the income and/or assets of an individual or family to fall below specified thresholds in order to qualify for benefits. There may be additional eligibility requirements to receive these programs, which provide cash and noncash assistance to eligible individuals and families.

2 The Food Stamp Program was renamed the Supplemental Nutrition Assistance Program (SNAP) in 2008.

3 The 2008 Panel followed the same individuals over a period of 64 months from May 2008 to November 2013. The data in this report were collected from February 2009 through April 2013 in Waves 2–14 of the 2008 SIPP. The population represented (the population universe) is the civilian, noninstitutionalized population living in the United States. The sample of households in SIPP is divided into four interview groups called rotation groups. Each month, one of the four rotation groups is interviewed about the previous 4 months (the reference period).

4 The longitudinal estimates presented here are based on people who were interviewed in all waves of the reference period or for whom imputed information exists. Efforts were made during the life of the panel to ensure that the sample remained representative of the civilian, noninstitutionalized population of the United States by attempting to follow people who moved to their new address. If the people included in the estimates have different experiences in program participation than those who did not respond initially, left the sample, or missed two or more consecutive waves, these longitudinal estimates may be biased.

Page 2:

In 2012, approximately 52.2 million people, or 21.3 percent of the population, participated in one or more major means-tested assistance programs, on average, each month.5

5 Estimates in this report (which may be shown in text, figures, and tables) are based on responses from a sample of the population and may differ from actual values because of sampling variability or other factors. As a result, apparent differences between the estimates for two or more groups may not be statistically significant. All comparative statements have undergone statistical testing and are significant at the 90 percent confidence level unless otherwise noted.

[73] Report: “Dynamics of Economic Well-Being: Participation in Government Programs, 2004 to 2007 and 2009—Who Gets Assistance?” By Jeongsoo Kim, Shelley K. Irving and Tracy A. Loveless. U.S. Census Bureau, July 2012. <www.census.gov>

Page 1:

This report focuses on the participation and characteristics of people who received benefits from any of the following means-tested assistance programs:1

• Temporary Assistance for Needy Families (TANF)

• General Assistance (GA)

• Supplemental Nutrition Assistance Program (SNAP)/Food Stamps2

• Supplemental Security Income (SSI)

• Medicaid3

• Housing Assistance

The data come from the 2004 and 2008 Panels of the Survey of Income and Program Participation (SIPP) and cover calendar years 2004 through 2007 and 2009.4 SIPP is a longitudinal survey, which means that, unlike periodic point-in-time surveys such as the Current Population Survey (CPS), SIPP follows the same people over time.5

Page 17:

Appendix Table A-1. Average Monthly Participation Rates for Any Major Means-Tested Program by Selected Characteristics 2004–2007 and 2009 … Participation rates in any means-tested program1 … 2004 … Total number of recipients (in thousands) [=] 41,841 … As percent of the population [=] 17.1

1 Major means-tested programs include Temporary Assistance for Needy Families (TANF), General Assistance (GA), Supplemental Security Income (SSI), Supplemental Nutrition Assistance Program (SNAP), Medicaid, and housing assistance.

[74] Calculated with the dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “6. Sources of Income for All Households by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[75] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income). …

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

[76] Webpage: “National Income and Product Accounts Gross Domestic Product: Second Quarter 2016 (Second Estimate) Corporate Profits: Second Quarter 2016 (Preliminary Estimate).” Bureau of Economic Analysis, March 30, 2017. <www.bea.gov>

Gross domestic product (GDP) is the value of the goods and services produced by the nation’s economy less the value of the goods and services used up in production. GDP is also equal to the sum of personal consumption expenditures, gross private domestic investment, net exports of goods and services, and government consumption expenditures and gross investment.

[77] Book: Economics: Principles and Policy (12th edition). By William Baumol and Alan Blinder. South-Western Cengage Learning, 2011. <books.google.com>

Page 491:

To sharpen the point, observe that real GDP is, by definition, the product of the total hours of work in the economy times the amount of output produced per hour—what we have just called labor productivity:

GDP = Hours of work × Output per hour = Hours worked × Labor productivity

For example, in the United States today, in round numbers, GDP is about $15 trillion and total hours of work per year are about 230 billion. Thus labor productivity is roughly $15 trillion/230 billion hours, or about $65 per hour.

[78] Textbook: Macroeconomics for Today (6th edition). By Irvin B. Tucker. South-Western Cengage Learning, 2010.

Page 530: “GDP per capita provides a general index of a country’s standard of living. Countries with low GDP per capita and slow growth in GDP per capita are less able to satisfy basic needs for food, shelter, clothing, education, and health.”

[79] Calculated with the dataset: “Real Gross Domestic Product Per Capita, Chained 2009 Dollars, Seasonally Adjusted Annual Rate, 1947–2016.” Federal Reserve Bank of St. Louis, January 27, 2017. <fred.stlouisfed.org>

CALCULATION: ($51,516 (GDP, 2016) – $13,456 (GDP, 1947)) / $13,456 (GDP, 1947) = 283%

NOTE: An Excel file containing the data and calculation is available upon request.

[80] Dataset: “Real Gross Domestic Product Per Capita, Chained 2009 Dollars, Seasonally Adjusted Annual Rate, 1947–2016.” Federal Reserve Bank of St. Louis, January 27, 2017. <fred.stlouisfed.org>

NOTE: An Excel file containing the data is available upon request.

[81] Calculated with the dataset: “Table 1.1.1. Percent Change From Preceding Period in Real Gross Domestic Product.” U.S. Department of Commerce, Bureau of Economic Analysis. Last revised April 28, 2016. <www.bea.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[82] Calculated with data from:

a) Dataset: “Table 1.1.1. Percent Change From Preceding Period in Real Gross Domestic Product.” U.S. Department of Commerce, Bureau of Economic Analysis. Last revised April 28, 2016. <www.bea.gov>

b) Dataset: “Table 7.1. Selected Per Capita Product and Income Series in Current and Chained Dollars.” U.S. Department of Commerce, Bureau of Economic Analysis. Last revised April 28, 2016. <www.bea.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[83] Paper: “Public Debt Overhangs: Advanced-Economy Episodes Since 1800.” By Carmen M. Reinhart (University of Maryland), Kenneth S. Rogoff (Harvard University), and Vincent R. Reinhart (chief U.S. economist at Morgan Stanley). Journal of Economic Perspectives, Summer 2012. Pages 69–86. <online.wsj.com>

Page 70:

In this paper, we use the long-dated cross-country data on public debt developed by Reinhart and Rogoff (2009) to examine the growth and interest rates associated with prolonged periods of exceptionally high public debt, defined as episodes where public debt to GDP exceeded 90 percent for at least five years. (The basic results here are reasonably robust to choices other than 90 percent as the critical threshold, as in Reinhart and Rogoff 2010a, b).1 Over the years 1800–2011, we find 26 such episodes across the advanced economies. While data limitations may have prevented us from including every episode of high public debt in advanced economies since 1800, we are confident that this list encompasses the preponderance of such episodes. To focus on the association between high debt and long-term growth, we only cursorily treat shorter episodes lasting under five years, of which there turn out to be only a few. The long length of typical public debt overhang episodes suggests that even if such episodes are originally caused by a traumatic event such as a war or financial crisis, they can take on a self-propelling character.

Consistent with a small but growing body of research, we find that the vast majority of high debt episodes—23 of the 26—coincide with substantially slower growth. On average across individual countries, debt/GDP levels above 90 percent are associated with an average annual growth rate 1.2 percent lower than in periods with debt below 90 percent debt; the average annual levels are 2.3 percent during the periods of exceptionally high debt versus 3.5 percent otherwise.

CALCULATION: (3.5 – 2.3) / 3.5 = 34.3%

[84] Calculated with data from:

a) Webpage: “The Debt to the Penny and Who Holds It.” Bureau of the Public Debt, United States Department of the Treasury. Accessed November 3, 2017 at <www.treasurydirect.gov>

As of 11/1/2017, the “Total Public Debt Outstanding” is $20,453,288,033,639.

b) Dataset: “Table 1.1.5. Gross Domestic Product.” U.S. Department of Commerce, Bureau of Economic Analysis. Last revised October 27, 2017. <www.bea.gov>

“[Billions of dollars] Seasonally adjusted at annual rates … Gross Domestic Product … 2017Q3 [=] 19,495.5”

CALCULATION: $20,453,288,033,639 debt / $19,495,500,000,000 GDP = 105%

[85] Working paper: “Does High Public Debt Consistently Stifle Economic Growth? A Critique of Reinhart and Rogoff.” By Thomas Herndon, Michael Ash, and Robert Pollin. Political Economy Research Institute, April 15, 2013. Revised 4/22/13. <www.peri.umass.edu>

Page 21: “Table 3: Published and replicated average real GDP growth, by public debt/GDP category”

NOTE: An Excel file containing the data and calculations is available here. See the tab entitled “HAP results.”

[86] Report: “Concepts and Methods of the U.S. National Income and Product Accounts (Chapters 1–11 and 13).” U.S. Bureau of Economic Analysis, November 2014. <www.bea.gov>

Page 5-2:

PCE [personal consumption expenditures] measures the goods and services purchased by “persons”—that is, by households and by nonprofit institutions serving households (NPISHs)—who are resident in the United States. Persons resident in the United States are those who are physically located in the United States and who have resided, or expect to reside, in this country for 1 year or more. PCE also includes purchases by U.S. government civilian and military personnel stationed abroad, regardless of the duration of their assignments, and by U.S. residents who are traveling or working abroad for 1 year or less.

Table 5.1 shows the kinds of transactions that are included in and excluded from PCE. Most of PCE consists of purchases of new goods and of services by households from private business. In addition, PCE includes purchases of new goods and of services by households from government and government enterprises, the costs incurred by NPISHs in providing services on behalf of households, net purchases of used goods by households, and purchases abroad of goods and services by U.S. residents traveling, working, or attending school in foreign countries. PCE also includes expenditures financed by third-party payers on behalf of households, such as employer-paid health insurance and medical care financed through government programs, and it includes expenses associated with life insurance and with private and government employee pension plans. Finally, PCE includes imputed purchases that keep PCE invariant to changes in the way that certain activities are carried out—for example, whether housing is rented or owned or whether employees are paid in cash or in kind. PCE transactions are valued in market prices, including sales and excise taxes.

In the NIPAs [national income and product accounts], final consumption expenditures by NPISHs is the portion of PCE that represents the services that are provided to households by NPISHs without explicit charge (such as the value of the education services provided by a nonprofit college or university that is over and above the tuition and other costs paid by or for the student’s household). It is equal to their gross output, which is measured as their current operating expenses (not including purchases of buildings and equipment, which are treated as private fixed investment), less their sales to households and to other sectors of the economy (such as sales of education services to employers) and less the value of any investment goods (such as software) that are produced directly by the NPISH. Services that are provided by NPISHs and are paid by or on behalf of households (such as the tuition and other costs) are already accounted for in PCE as purchases by households. (For more information, see the section on NPISHs in the technical note at the end of this chapter.)

[87] Article: “Why Does GDP Include Imputations?” U.S. Bureau of Economic Analysis, April 23, 2008. <www.bea.gov>

Imputations approximate the price and quantity that would be obtained for a good or service if it was traded in the market place. The largest imputation in the GDP accounts is that made to approximate the value of the services provided by owner-occupied housing. That imputation is made so that the treatment of owner-occupied housing in the GDP is comparable to that of tenant-occupied housing, which is valued by rent paid. That practice keeps GDP invariant as to whether a house is owner-occupied or rented. In the GDP, the purchase of a new house is treated as an investment; the ownership of the home is treated as a productive activity; and a service is assumed to flow from the house to the occupant over the economic life of the house. For the homeowner, the value of that service is measured as the income the homeowner could have received if the house had been rented to a tenant. …

In addition to imputations for nonmarket transactions, the GDP accounts redirect certain transactions so that the consumption is attributed to the ultimate recipient of the good or service rather than to the payer. An important example is health care, which is generally paid for by private health insurance (often provided by the employer), by government insurance plans such as Medicare and Medicaid, or by consumer out-of-pocket payments for deductibles, copayments, and uninsured expenses. In the GDP, these health-care transactions are redirected so that they are included in personal consumption expenditures, reflecting the role of households as the final consumers of those health goods and services.

[88] “World Development Report 2000/2001: Attacking Poverty.” World Bank, September 2000. <openknowledge.worldbank.org>

Page 17:

The World Bank’s approach

The World Bank has been estimating global income poverty figures since 1990. The latest round of estimation, in October 1999, used new sample survey data and price information to obtain comparable figures for 1987, 1990, 1993, 1996, and 1998 (the figures for 1998 are preliminary estimates). The method is the same as in past estimates (World Bank 1990, 1996d).

Consumption. Poverty estimates are based on consumption or income data collected through household surveys. Data for 96 countries, from a total of 265 nationally representative surveys, corresponding to 88 percent of the developing world’s people are now available, up from only 22 countries in 1990. Of particular note is the increase in the share of people covered in Africa from 66 to 73 percent, a result of extensive efforts to improve household data in the region.

Consumption is conventionally viewed as the preferred welfare indicator, for practical reasons of reliability and because consumption is thought to better capture long-run welfare levels than current income.

[89] Webpage: “What We Do.” World Bank. Accessed April 25, 2017 at <www.worldbank.org>

The World Bank Group has set two goals for the world to achieve by 2030:

• End extreme poverty by decreasing the percentage of people living on less than $1.90 a day to no more than 3%

• Promote shared prosperity by fostering the income growth of the bottom 40% for every country

The World Bank is a vital source of financial and technical assistance to developing countries around the world. We are not a bank in the ordinary sense but a unique partnership to reduce poverty and support development. The World Bank Group comprises five institutions managed by their member countries.

[90] Report: “100 Years of U.S. Consumer Spending.” U.S. Department of Labor, Bureau of Labor Statistics, August 2006. <www.bls.gov>

Page 1:

The clearest indicators of an improved standard of living are income levels and household expenditures. Between 1901 and 2003, the average U.S. household’s income increased 67-fold, from $750 to $50,302. During the same period, household expenditures increased 53-fold, from $769 to $40,748. Equally dramatic is that the $40,748 would have bought more than $2,000 worth of goods in 1901 prices, indicating a tripling of purchasing power.

One significant effect of this upsurge was the change to a consumer goods-oriented U.S. economy. Mass consumption, spurred by advertising and consumer credit, has become a distinguishing characteristic of modern society. Today, consumer spending has become the largest component of U.S. gross domestic product.1

As a result, household expenditure and income data constitute a valuable resource in assessing the health and vitality of the U.S. economy, as well as those of individual households or families.2 While no two families spend money in exactly the same manner, indicators suggest that families allocate their expenditures with some regularity and predictability. Consumption patterns indicate the priorities that families place on the satisfaction of the following needs: Food, clothing, housing, heating and energy, health, transportation, furniture and appliances, communication, culture and education, and entertainment.3

1 See Valentino Piana, “Consumption,” at <www.economicswebinstitute.org> (visited February 14, 2005).

2 The terms “households” and “families” are used interchangeably in this report.

3 Valentino Piana, “Consumption.”

[91] Calculated with data from:

a) Dataset: “Table 2.1. Personal Income and Its Disposition.” U.S. Department of Commerce, Bureau of Economic Analysis. Last revised April 28, 2017. <www.bea.gov>

Line 29: “Personal Consumption Expenditures”

Line 40: “Population”

b) Dataset: “Table 2.3.4. Price Indexes for Personal Consumption Expenditures by Major Type of Product.” U.S. Department of Commerce, Bureau of Economic Analysis. Last revised June 28, 2016. <www.bea.gov>

Line 1: “Personal consumption expenditures (PCE)”

NOTE: An Excel file containing the data and calculations is available upon request.

[92] Webpage: “Glossary.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed July 19, 2017 at <www.bls.gov>

Expenditures (Consumer Expenditure Survey)

Expenditures consist of the transaction costs, including excise and sales taxes, of goods and services acquired during the interview or recordkeeping period. Expenditure estimates include expenditures for gifts, but exclude purchases or portions of purchases directly assignable to business purposes. Also excluded are periodic credit or installment payments on goods or services already acquired. The full cost of each purchase is recorded even though full payment may not have been made at the date of purchase. Expenditure categories include food, alcoholic beverages, housing, apparel and services, transportation, health care, entertainment, personal care products and services, reading, education, tobacco products and smoking supplies, cash contributions, personal insurance and pensions, and miscellaneous).

[93] Webpage: “Consumer Expenditures and Income: Overview.” U.S. Department of Labor, Bureau of Labor Statistics. Last modified February 25, 2016. <www.bls.gov>

The Consumer Expenditure Survey (CE) is a nationwide household survey conducted by the U.S. Bureau of Labor Statistics (BLS) to find out how Americans spend their money. It is the only federal government survey that provides information on the complete range of consumers’ expenditures as well as their incomes and demographic characteristics. BLS publishes 12-month estimates of consumer expenditures twice a year with the estimates summarized by various income levels and household characteristics. BLS also produces annual public-use microdata files to help researchers analyze the data in more detail.

The CE consists of estimates derived from two separate surveys, the Interview Survey and the Diary Survey. The Quarterly Interview Survey is designed to collect data on large and recurring expenditures that consumers can be expected to recall for a period of 3 months or longer, such as rent and utilities, and the Diary Survey is designed to collect data on small, frequently purchased items, including most food and clothing. Together, the data from the two surveys cover the complete range of consumers’ expenditures. CE data are collected for BLS by the U.S. Census Bureau.

[94] Webpage: “Frequently Asked Questions.” U.S. Department of Labor, Bureau of Labor Statistics. Last modified April 6, 2017. <www.bls.gov>

How is the Consumer Expenditure Survey used?

Data from the Consumer Expenditure Survey are used in a number of different ways by a variety of users. … Government and private agencies use the data to study the welfare of particular segments of the population, such as those consumer units with a reference person aged 65 and older or under age 25, or for low-income consumer units (see the response to question 4 for the definition of a reference person). Economic policymakers use the data to study the impact of policy changes on the welfare of different socioeconomic groups. Researchers use the data in a variety of studies, including those that focus on the spending behavior of different family types, trends in expenditures on various expenditure components including new types of goods and services, gift-giving behavior, consumption studies, and historical spending trends.

Are reimbursed expenditures, such as those for medical expenses or car repairs, included in the published totals?

No. Expenditures shown in the published tables are direct out-of-pocket expenditures. The amounts are net of reimbursements.

[95] Email from the U.S. Bureau of Labor Statistics to Just Facts, August 8, 2017.

“Thank you for your interest in the Consumer Expenditure Surveys. You are correct that we treat SSI payments and SNAP benefits as regular income. You are also correct that we track out of pocket expenditures only. We do not collect consumption data that would include benefits received from Medicare and Medicaid.”

[96] “2015 Consumer Expenditure Survey.” U.S. Department of Labor, Bureau of Labor Statistics, August 2016. <www.bls.gov>

“Table 1110. Deciles of income before taxes: Annual expenditure means, shares, standard errors, and coefficients of variation.” <www.bls.gov>

Money income before taxes:

• Wages and salaries

• Self-employment income

• Social Security, private, and government retirement

• Interest, dividends, rental income, other property income

• Public assistance, Supplemental Security Income, Supplementary Nutrition Assistance Program (SNAP)

• Unemployment and workers’ compensation, veterans’ benefits, and regular contributions for support

• Other income

[97] Calculated with data from the: “2015 Consumer Expenditure Survey.” U.S. Department of Labor, Bureau of Labor Statistics, August 2016. <www.bls.gov>

“Table 1110. Deciles of income before taxes: Annual expenditure means, shares, standard errors, and coefficients of variation.” <www.bls.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[98] Webpage: “Bruce D. Meyer.” University of Chicago, Harris School of Public Policy. Accessed July 11, 2017 at <harris.uchicago.edu>

[99] Paper: “Measuring the Well-Being of the Poor Using Income and Consumption.” By Bruce D. Meyer and James X. Sullivan. Journal of Human Resources, June 2003. Pages 1180–1220. <harris.uchicago.edu>

Pages 1196–1197:

Although we expect that income and consumption are fairly well measured for the vast majority of people, both income and consumption are surely measured with some error. Furthermore, observations at the bottom are more likely to have significant measurement error because the more unusual is an observation the more likely its values are due to error than truth.

[100] Paper: “Identifying the Disadvantaged: Official Poverty, Consumption Poverty, and the New Supplemental Poverty Measure.” By Bruce D. Meyer and James X. Sullivan. Journal of Economic Perspectives, Summer 2012. Pages 111–136. <harris.uchicago.edu>

Page 117:

Comparisons of income and consumption at the bottom of the distribution provide additional evidence that income is underreported. Reported consumption exceeds reported income at the bottom of the distribution, even for those with little or no assets or debts (Meyer and Sullivan 2003, 2011). For recent years, the 5th percentile of the expenditures distribution in the Consumer Expenditure Survey is more than 40 percent higher than the 5th percentile of the income distribution in the Current Population Survey. For families in the Consumer Expenditure Survey in the bottom 5 percent of the income distribution, expenditures exceed income by more than a factor of seven (Meyer and Sullivan 2011).6

6 While comparisons of survey data on aggregate expenditures to National Income and Product Accounts (NIPA) consumption indicate underreporting of expenditures as well, the poor consume a different bundle of goods than the general public, so that the typical comparisons do not reflect the composition of consumption for the poor. In fact, key components of spending match up well with national income and product account (NIPA) aggregates, and these components account for a large fraction of total spending for the poor—about 70 percent of consumption for those near the poverty line (Meyer and Sullivan 2012). For food at home, on average the Consumer Expenditure Survey/NIPA ratio is over 0.85, and for rent plus utilities, the ratio is nearly 1.00 (Bee, Meyer, and Sullivan forthcoming).

[101] Paper: “Measuring the Well-Being of the Poor Using Income and Consumption.” By Bruce D. Meyer and James X. Sullivan. Journal of Human Resources, June 2003. Pages 1180–1220. <harris.uchicago.edu>

Page 1181:

Consumption is less vulnerable to under-reporting bias, and ethnographic research on poor households in the U.S. suggests that consumption is better reported than income. There are also conceptual and economic reasons to prefer consumption to income because consumption is a more direct measure of material well-being.

We find substantial evidence that consumption is better measured than income for those with few resources. We also find that consumption performs better as an indicator of low material well-being. These findings favor the examination of consumption data when policymakers are deciding on appropriate benefit amounts for programs such as Food Stamps, just as consumption standards were behind the original setting of the poverty line. Similarly, the results favor using consumption measures to evaluate the effectiveness of transfer programs and general trends in poverty and food spending. Nevertheless, the ease of reporting income favors its use as the main eligibility criteria for transfer programs such as Food Stamps and Temporary Assistance for Needy Families (TANF).

[102] Webpage: “Consumer Expenditure Survey, Frequently Asked Questions.” U.S. Department of Labor, Bureau of Labor Statistics. Last modified April 6, 2017. <www.bls.gov>

Why do average annual expenditures exceed income for some of the demographic groups? How can consumer units spend more than they earn?

Data users may notice that average annual expenditures presented in the income tables sometimes exceed income before taxes for the lower income groups. Consumer units whose members experience a spell of unemployment may draw on their savings to maintain their expenditures. Self-employed consumers may experience business losses that result in low or even negative incomes, but are able to maintain their expenditures by borrowing or relying on savings. Students may get by on loans while they are in school, and retirees may rely on drawing down savings and investments.

[103] Article: “CE Data: Quintiles of Income Versus Quintiles of Outlays.” By John M. Rogers and Maureen B. Gray. U.S. Bureau of Labor Statistics Monthly Labor Review, December 1994. <blsmon1.bls.gov>

Page 33:

Results from the CE [Consumer Expenditure] Survey have typically shown that when the data are classified by income quintile, the expenditures-to-income ratio is quite high for the lowest income quintile. Table 1 shows the relationship between expenditures and income for 1992, using data from the interview component of the CE Survey. The trend in the expenditures-to-income ratios from the first to the fifth quintile is decreasing, as expected, with expenditures exceeding income in the first and second quintiles. That expenditures exceed income in these quintiles is not unreasonable, given consumers’ access to savings, borrowing, and credit, mentioned earlier. However, the degree by which expenditures exceed income—a factor greater than 2 for the lowest quintile—seems extreme. Indeed, one of the most commonly asked questions about CE Survey data pertains to expenditures exceeding income for the lower income classes.

Page 37:

The article also shows that consumer units in the lowest income quintile are not necessarily the same consumer units in the lowest outlays quintile. Indeed, some consumer units in the lowest income quintile have expenditures that are more typical of upper-income consumers.

[104] Calculated with data from:

a) “Consumer Expenditure Survey.” U.S. Department of Labor, Bureau of Labor Statistics, 1989. <www.bls.gov>

“Table 1100. Quintiles of Income Before Taxes: Share of Annual Aggregate Expenditures and Sources of Income.” <www.bls.gov>

b) “Consumer Expenditure Survey.” U.S. Department of Labor, Bureau of Labor Statistics, 2015. <www.bls.gov>

“Table 1101. Quintiles of Income Before Taxes: Shares of Annual Aggregate Expenditures and Sources of Income.” <www.bls.gov>

c) Dataset: “Table 2.3.4. Price Indexes for Personal Consumption Expenditures by Major Type of Product.” U.S. Department of Commerce, Bureau of Economic Analysis. Last revised June 28, 2016. <www.bea.gov>

Line 1: “Personal consumption expenditures (PCE)”

NOTE: An Excel file containing the data and calculations is available upon request.

[105] Webpage: “Consumer Expenditure Survey, Frequently Asked Questions.” U.S. Department of Labor, Bureau of Labor Statistics. Last modified April 6, 2017. <www.bls.gov>

What is a consumer unit?

A consumer unit consists of any of the following: (1) all members of a particular household who are related by blood, marriage, adoption, or other legal arrangements; (2) a person living alone or sharing a household with others or living as a roomer in a private home or lodging house or in permanent living quarters in a hotel or motel, but who is financially independent; or (3) two or more persons living together who use their incomes to make joint expenditure decisions. Financial independence is determined by spending behavior with regard to the three major expense categories: housing, food, and other living expenses. To be considered financially independent, the respondent must provide at least two of the three major expenditure categories, either entirely or in part.

The terms consumer unit, family, and household are often used interchangeably for convenience. However, the proper technical term for purposes of the Consumer Expenditure Survey is consumer unit.

[106] Report: “100 Years of U.S. Consumer Spending.” U.S. Department of Labor, Bureau of Labor Statistics, August 2006. <www.bls.gov>

Page 1:

The clearest indicators of an improved standard of living are income levels and household expenditures. Between 1901 and 2003, the average U.S. household’s income increased 67- fold, from $750 to $50,302. During the same period, household expenditures increased 53-fold, from $769 to $40,748. Equally dramatic is that the $40,748 would have bought more than $2,000 worth of goods in 1901 prices, indicating a tripling of purchasing power.

One significant effect of this upsurge was the change to a consumer goods-oriented U.S. economy. Mass consumption, spurred by advertising and consumer credit, has become a distinguishing characteristic of modern society. Today, consumer spending has become the largest component of U.S. gross domestic product.1

As a result, household expenditure and income data constitute a valuable resource in assessing the health and vitality of the U.S. economy, as well as those of individual households or families.2 While no two families spend money in exactly the same manner, indicators suggest that families allocate their expenditures with some regularity and predictability. Consumption patterns indicate the priorities that families place on the satisfaction of the following needs: Food, clothing, housing, heating and energy, health, transportation, furniture and appliances, communication, culture and education, and entertainment.3

1 See Valentino Piana, “Consumption,” at <www.economicswebinstitute.org> (visited February 14, 2005).

2 The terms “households” and “families” are used interchangeably in this report.

3 Valentino Piana, “Consumption.”

[107] Calculated with: “2015 Consumer Expenditure Survey.” U.S. Department of Labor, Bureau of Labor Statistics, August 2016. <www.bls.gov>

“Table 1110. Deciles of income before taxes: Annual expenditure means, shares, standard errors, and coefficients of variation.” <www.bls.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[108] Webpage: “Consumer Expenditure Survey, Frequently Asked Questions.” U.S. Department of Labor, Bureau of Labor Statistics. Last modified April 6, 2017. <www.bls.gov>

What is a consumer unit?

A consumer unit consists of any of the following: (1) all members of a particular household who are related by blood, marriage, adoption, or other legal arrangements; (2) a person living alone or sharing a household with others or living as a roomer in a private home or lodging house or in permanent living quarters in a hotel or motel, but who is financially independent; or (3) two or more persons living together who use their incomes to make joint expenditure decisions. Financial independence is determined by spending behavior with regard to the three major expense categories: housing, food, and other living expenses. To be considered financially independent, the respondent must provide at least two of the three major expenditure categories, either entirely or in part.

The terms consumer unit, family, and household are often used interchangeably for convenience. However, the proper technical term for purposes of the Consumer Expenditure Survey is consumer unit.

[109] Chart constructed with data from:

a) Report: “100 Years of U.S. Consumer Spending.” U.S. Department of Labor, Bureau of Labor Statistics, August 2006. <www.bls.gov>

Page 6: “Chart 4. Expenditure shares, United States, New York, and Massachusetts, 1901.”

Page 13: “Chart 8. Expenditure shares, United States, New York, and Massachusetts, 1918–19.”

Page 20: “Chart 12. Expenditure shares, United States, New York, and Massachusetts, 1934–36.”

Page 26: “Chart 16. Expenditure shares, United States, New York, and Massachusetts, 1950.”

Page 32: “Chart 20. Expenditure shares, United States, New York, and Massachusetts, 1960–61.”

Page 39: “Chart 24. Expenditure shares, United States, New York, and Massachusetts, 1972–73.”

Page 47: “Chart 28. Expenditure shares, United States, New York, and Massachusetts, 1984–85.”

Page 55: “Chart 32. Expenditure shares, United States, New York, and Massachusetts, 1996–97.”

Page 62: “Chart 36. Expenditure shares, United States, New York, and Massachusetts, 2002–03.”

b) “2015 Consumer Expenditure Survey.” U.S. Department of Labor, Bureau of Labor Statistics, August 2016. <www.bls.gov>

“Table 1110. Deciles of income before taxes: Annual expenditure means, shares, standard errors, and coefficients of variation.” <www.bls.gov>

NOTE: An Excel file containing the data is available upon request.

[110] Webpage: “Consumer Expenditure Survey, Frequently Asked Questions.” U.S. Department of Labor, Bureau of Labor Statistics. Last modified April 6, 2017. <www.bls.gov>

What is a consumer unit?

A consumer unit consists of any of the following: (1) all members of a particular household who are related by blood, marriage, adoption, or other legal arrangements; (2) a person living alone or sharing a household with others or living as a roomer in a private home or lodging house or in permanent living quarters in a hotel or motel, but who is financially independent; or (3) two or more persons living together who use their incomes to make joint expenditure decisions. Financial independence is determined by spending behavior with regard to the three major expense categories: housing, food, and other living expenses. To be considered financially independent, the respondent must provide at least two of the three major expenditure categories, either entirely or in part.

The terms consumer unit, family, and household are often used interchangeably for convenience. However, the proper technical term for purposes of the Consumer Expenditure Survey is consumer unit.

[111] Webpage: “Consumer Expenditure Survey, Frequently Asked Questions.” U.S. Department of Labor, Bureau of Labor Statistics. Last modified April 6, 2017. <www.bls.gov>

Are historical data from the Consumer Expenditure Survey available?

Yes. Prior to 1980, the Consumer Expenditure Survey was conducted about every 10 years. Since that time, it has been an ongoing survey. Online data tables are available from both the 1972–73 and later surveys. For information about the availability of any Consumer Expenditure Survey data, including historical data, contact the Division of Consumer Expenditure Survey.

Caution should be used in comparing data from the current survey with those gathered before the 1972–73 surveys, or even during the first few years of the current survey, due to changes in concepts and definitions. For example, integrated data from the Diary and Interview Surveys have been published from 1972–73 and from 1984 onward; prior to 1972–73, data from each survey were published separately. The Consumer Expenditure Survey has electronic versions of integrated tables for 1972–73 and annually from 1984 onward. Also prior to 1972–73, published data covered only the urban portion of the population. Beginning in 1972–73 and from 1984 onward, the published data are for the total population, urban and rural.

[112] Report: “100 Years of U.S. Consumer Spending.” U.S. Department of Labor, Bureau of Labor Statistics, August 2006. <www.bls.gov>

Page 70:

Perhaps as revealing as the shift in consumer expenditure shares over the past 100 years is the wide variety of consumer items that had not been invented during the early decades of the 20th century but are commonplace today. In the 21st century, households throughout the country have purchased computers, televisions, iPods, DVD players, vacation homes, boats, planes, and recreational vehicles. They have sent their children to summer camps; contributed to retirement and pension funds; attended theatrical and musical performances and sporting events; joined health, country, and yacht clubs; and taken domestic and foreign vacation excursions. These items, which were unknown and undreamt of a century ago, are tangible proof that U.S. households today enjoy a higher standard of living.

[113] Calculated with data from the “2015 Residential Energy Consumption Survey.” U.S. Energy Information Administration. February 2017. <www.eia.gov>

“Table HC7.5 Air Conditioning in U.S. Homes, by Household Income, 2015.” <www.eia.gov>

“Table HC3.5 Appliances in U.S. Homes, by Household Income, 2015.” <www.eia.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[114] Calculated with data from the “2015 Residential Energy Consumption Survey.” U.S. Energy Information Administration. February 2017. <www.eia.gov>

“Table HC4.5 Electronics in U.S. Homes by Household Income, 2015.” <www.eia.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[115] “Report on the Economic Well-Being of U.S. Households in 2015.” Board of Governors of the Federal Reserve System, May 2016. <www.federalreserve.gov>

Page 8: “Table 2. Overall Well-Being.”

Pages 69–70:

The Survey of Household Economic Decisionmaking (SHED) was designed by Board staff and administered by GfK, an online consumer research company, on behalf of the Board. In order to create a nationally representative probability-based sample, GfK’s KnowledgePanel selected respondents based on both random digit dialing and address-based sampling (ABS). …

A total of 8,681 KnowledgePanel members received e-mail invitations to complete this survey, including an oversample of respondents with a household income under $40,000. The sample included a random selection of 2,853 out of the 4,262 KnowledgePanel respondents who participated in the Board’s 2014 SHED (excluding those who were in the 2014 lower-income oversample) and an additional 3,332 randomly selected KnowledgePanel respondents who did not participate in the Board’s previous survey. It also included 2,496 randomly selected KnowledgePanel respondents whose household income was under $40,000. (See table 1 in main text.) The lower-income oversample was included in the study to ensure sufficient coverage of this population for key questions of interest. …

The selection methodology for general population samples from the KnowledgePanel ensures that the resulting samples behave as an equal probability of selection method (EPSEM) samples. This methodology starts by weighting the entire KnowledgePanel to the benchmarks secured from the latest March supplement of the Current Population Survey along several dimensions. This way, the weighted distribution of the KnowledgePanel matches that of U.S. adults. Typically, the geo-demographic dimensions used for weighting the entire KnowledgePanel include gender, age, race/ethnicity, education, census region, household income, home ownership status, metropolitan area status, and Internet access. …

Once the sample has been selected and fielded, and all the study data are collected and made final, a post-stratification process is used to adjust for any survey non-response as well as any non-coverage or under- and over-sampling resulting from the study specific sample design. The following variables were used for the adjustment of weights for this study: gender, age, race/ethnicity, education, census region, residence in a metropolitan area, household income, and access to the Internet. Demographic and geographic distributions for the noninstitutionalized, civilian population ages 18 and over from the March 2014 Current Population Survey are used as benchmarks in this adjustment.

Although weights allow the sample population to match the U.S. population based on observable characteristics, similar to all survey methods, it remains possible that non-coverage or non-response results in differences between the sample population and the U.S. population that are not corrected using weights.

[116] Webpage: “National Income and Product Accounts Gross Domestic Product: Second Quarter 2016 (Second Estimate) Corporate Profits: Second Quarter 2016 (Preliminary Estimate).” Bureau of Economic Analysis, March 30, 2017. <www.bea.gov>

Gross domestic product (GDP) is the value of the goods and services produced by the nation’s economy less the value of the goods and services used up in production. GDP is also equal to the sum of personal consumption expenditures, gross private domestic investment, net exports of goods and services, and government consumption expenditures and gross investment.

[117] Book: Economics: Principles and Policy (12th edition). By William Baumol and Alan Blinder. South-Western Cengage Learning, 2011. <books.google.com>

Page 491:

To sharpen the point, observe that real GDP is, by definition, the product of the total hours of work in the economy times the amount of output produced per hour—what we have just called labor productivity:

GDP = Hours of work × Output per hour = Hours worked × Labor productivity

For example, in the United States today, in round numbers, GDP is about $15 trillion and total hours of work per year are about 230 billion. Thus labor productivity is roughly $15 trillion/230 billion hours, or about $65 per hour.

[118] Report: “International Comparisons of GDP Per Capita and Per Hour, 1960–2011.” U.S. Bureau of Labor Statistics, November 7, 2012. <www.bls.gov>

Page 1: “GDP per capita, when converted to U.S. dollars using purchasing power parities, is the most widely used income measure for international comparisons of living standards.”

Page 2:

Gross Domestic Product (GDP) is defined as the value of all market and some nonmarket goods and services produced within a country’s geographic borders. As such, it is the most comprehensive measure of a country’s economic output that is estimated by statistical agencies. GDP per capita may therefore be viewed as a rough indicator of a nation’s economic well-being, while GDP per hour worked can provide a general picture of a country’s productivity.

[119] Dataset: “GDP Per Capita, PPP (Constant 2011 International $).” World Bank, January 11, 2018. <data.worldbank.org>

NOTE: An Excel file containing the data is available upon request.

[120] Dataset: “GDP per Capita, Purchasing Power Parity, 2015.” Organization for Economic Cooperation and Development. Accessed January 23, 2017 at <data.oecd.org>

NOTE: An Excel file containing the data is available upon request.

[121] Webpage: “About the OECD.” Organization for Economic Cooperation and Development. Accessed June 7, 2017 at <www.oecd.org>

Our Mission

The mission of the Organisation for Economic Co-operation and Development (OECD) is to promote policies that will improve the economic and social well-being of people around the world.

The OECD provides a forum in which governments can work together to share experiences and seek solutions to common problems. We work with governments to understand what drives economic, social and environmental change. We measure productivity and global flows of trade and investment. We analyse and compare data to predict future trends. We set international standards on a wide range of things, from agriculture and tax to the safety of chemicals.

We also look at issues that directly affect everyone’s daily life, like how much people pay in taxes and social security, and how much leisure time they can take. We compare how different countries’ school systems are readying their young people for modern life, and how different countries’ pension systems will look after their citizens in old age.

Drawing on facts and real-life experience, we recommend policies designed to improve the quality of people’s lives. We work with business, through the Business and Industry Advisory Committee to the OECD (BIAC), and with labour, through the Trade Union Advisory Committee (TUAC). We have active contacts as well with other civil society organisations. The common thread of our work is a shared commitment to market economies backed by democratic institutions and focused on the wellbeing of all citizens. Along the way, we also set out to make life harder for the terrorists, tax dodgers, crooked businessmen and others whose actions undermine a fair and open society.

[122] Webpage: “Household Disposable Income.” Organization for Economic Cooperation and Development. Accessed January 23, 2017 at <data.oecd.org>

Disposable income, as a concept, is closer to the idea of income as generally understood in economics, than is either national income or gross domestic product (GDP). This indicator is measured in terms of net in annual growth rates and in terms of gross adjusted in USD per capita at current prices and PPPs. Data are under 2008 System of National Accounts (SNA 2008) for all countries except for Chile, Japan and Turkey (SNA 1993).

[123] Webpage: “Household Disposable Income.” Organization for Economic Cooperation and Development. Accessed January 23, 2017 at <data.oecd.org>

Real household net disposable income is defined as the sum of household final consumption expenditure and savings, minus the change in net equity of households in pension funds. This indicator also corresponds to the sum of wages and salaries, mixed income, net property income, net current transfers and social benefits other than social transfers in kind, less taxes on income and wealth and social security contributions paid by employees, the self-employed and the unemployed. Household gross adjusted disposable income additionally reallocates “income” from government and non-profit institutions serving households (NPISHs) to households to reflect social transfers in kind. These transfers reflect expenditures made by government or NPISHs on individual goods and services, such as health and education, on behalf of an individual household. The indicator includes the disposable income of non-profit institutions serving households. Disposable income, as a concept, is closer to the idea of income as generally understood in economics, than is either national income or gross domestic product (GDP). This indicator is measured in terms of net in annual growth rates and in terms of gross adjusted in USD per capita at current prices and PPPs. Data are under 2008 System of National Accounts (SNA 2008) for all countries except for Chile, Japan and Turkey (SNA 1993).

[124] Webpage: “Personal Income and Outlays, December 2016.” U.S. Department of Commerce, Bureau of Economic Analysis, March 31, 2017. <www.bea.gov>

Personal income is the income received by, or on behalf of, all persons from all sources: from participation as laborers in production, from owning a home or business, from the ownership of financial assets, and from government and business in the form of transfers. It includes income from domestic sources as well as the rest of world. It does not include realized or unrealized capital gains or losses.

Disposable personal income is the income available to persons for spending or saving. It is equal to personal income less personal current taxes.

[125] Webpage: “Glossary of Statistical Terms” Organization for Economic Co-operation and Development. Accessed June 19, 2017 at <stats.oecd.org>

a) “Wages and Salaries – SNA [System of National Accounts].” Last updated July 19, 2002 <stats.oecd.org>

Definition:

Wages and salaries consist of the sum of wages and salaries in cash and wages and salaries in kind.

Context:

Wages and salaries include the values of any social contributions, income taxes, etc., payable by the employee even if they are actually withheld by the employer for administrative convenience or other reasons and paid directly to social insurance schemes, tax authorities, etc., on behalf of the employee. Wages and salaries may be paid in various ways, including goods or services provided to employees for remuneration in kind instead of, or in addition to, remuneration in cash (SNA 7.32-7.42).

b) “Mixed Income.” Last updated November 15, 2001. <stats.oecd.org>

Definition:

Mixed income is the surplus or deficit accruing from production by unincorporated enterprises owned by households; it implicitly contains an element of remuneration for work done by the owner, or other members of the household, that cannot be separately identified from the return to the owner as entrepreneur but it excludes the operating surplus coming from owner-occupied dwellings.

c) “Property Income.” Last updated February 11, 2002. <stats.oecd.org>

Definition:

Property income is the income receivable by the owner of a financial asset or a tangible non-produced asset in return for providing funds to or putting the tangible non-produced asset at the disposal of, another institutional unit; it consists of interest, the distributed income of corporations (i.e. dividends and withdrawals from income of quasi-corporations), reinvested earnings on direct foreign investment, property income attributed to insurance policy holders, and rent.

d) “Current Transfers – SNA [System of National Accounts].” System of National Accounts, 2008. Last updated April 22, 2013. <stats.oecd.org>

Definition:

Current transfers consist of all transfers that are not transfers of capital; they directly affect the level of disposable income and should influence the consumption of goods or services.

On the contrary see: Capital transfers.

Context:

A current transfer reduces the income and consumption possibilities of the first party and increases the income and consumption possibilities of the second party. Current transfers are therefore not linked to, or conditional on, the acquisition or disposal of assets by one or both parties to the transaction.

e) “Capital Transfers.” Last updated April 22, 2013. <stats.oecd.org>

Definition:

Capital transfers are unrequited transfers where either the party making the transfer realizes the funds involved by disposing of an asset (other than cash or inventories), by relinquishing a financial claim (other than accounts receivable) or the party receiving the transfer is obliged to acquire an asset (other than cash or inventories) or both conditions are met. Capital transfers are often large and irregular but neither of these are necessary conditions for a transfer to be considered a capital rather than a current transfer.

f) “Current Transfers Between Households.” Last updated April 22, 2013. <stats.oecd.org>

Definition:

Current transfers between households consist of all current transfers made, or received, by resident households to or from other resident or non-resident households.

g) “Social Benefits.” Last updated November 22, 2001. <stats.oecd.org>

Definition:

Social benefits are current transfers received by households intended to provide for the needs that arise from certain events or circumstances, for example, sickness, unemployment, retirement, housing, education or family circumstances.

h) “Social Transfers in Kind.” Last updated March 13, 2003. <stats.oecd.org>

Definition:

Social transfers in kind consist of individual goods and services provided as transfers in kind to individual households by government units (including social security funds) and non-profit institutions serving households (NPISHs), whether purchased on the market or produced as non-market output by government units or NPISHs.

The items included are:

(a) social security benefits, reimbursements,

(b) other social security benefits in kind,

(c) social assistance benefits in kind, and

(d) transfers of individual non-market goods or services.

[126] Dataset: “Gross Adjusted Disposable Income Per Household, Purchasing Power Parity, 2015.” Organization for Economic Cooperation and Development. Accessed January 24, 2018 at <data.oecd.org>

Real household net disposable income is defined as the sum of household final consumption expenditure and savings, minus the change in net equity of households in pension funds. This indicator also corresponds to the sum of wages and salaries, mixed income, net property income, net current transfers and social benefits other than social transfers in kind, less taxes on income and wealth and social security contributions paid by employees, the self-employed and the unemployed. Household gross adjusted disposable income additionally reallocates “income” from government and non-profit institutions serving households (NPISHs) to households to reflect social transfers in kind. These transfers reflect expenditures made by government or NPISHs on individual goods and services, such as health and education, on behalf of an individual household. The indicator includes the disposable income of non-profit institutions serving households. Disposable income, as a concept, is closer to the idea of income as generally understood in economics, than is either national income or gross domestic product (GDP). This indicator is measured in terms of net in annual growth rates and in terms of gross adjusted in USD per capita at current prices and PPPs. Data are under 2008 System of National Accounts (SNA 2008) for all countries except for Chile, Japan and Turkey (SNA 1993).

NOTE: An Excel file containing the data is available upon request.

[127] Working Paper: “Comparing Real Wages.” By Orley Ashenfelter. National Bureau of Economic Research, April 2012. <www.nber.org>

Abstract: “A real wage rate is a nominal wage rate divided by the price of a good and is a transparent measure of how much of the good an hour of work buys. It provides an important indicator of the living standards of workers, and also of the productivity of workers.”

[128] Working Paper: “Comparing Real Wages.” By Orley Ashenfelter. National Bureau of Economic Research, April 2012. <www.nber.org>

Page 3:

In this paper I provide some preliminary analysis of my own attempt to measure wage rates for comparable workers doing the same tasks in different places and at different times. My goal is to show just how useful a credible, transparent measure of the wage rate can be for economic analysis. The data I use come from an organization that is famous for producing the same product in different places and it has done so for many decades using a known production technology. The workers are thus using identical skills, using identical technology, and producing the same product. I am, of course speaking of workers at McDonald’s restaurants, and their famous product the Big Mac.

Page 17:

In order to create a manageable, readable table I have aggregated the more than 60 countries for which there are data into a group of economic regions. These are, admittedly, only a heuristic device for ease of interpretation, but the aggregation used here captures about 85 percent of the variability in the raw data on wage rates. The year 2007 was selected both because the sample of countries for which data were collected was expanded in that year, but also because the financial crisis that affected many countries had not yet begun.

Page 20: “An attractive feature of the BMPH measure of the real wage rate is that it does not rely on exchange rates at all. It is a direct physical measure of the output a worker may purchase with an hour of work, and it is comparable over time and across space.”

[129] Working Paper: “Comparing Real Wages.” By Orley Ashenfelter. National Bureau of Economic Research, April 2012. <www.nber.org>

Page 17:

Table 3 provides a basic cross-section of data for 2007 on prices and wages from McDonald’s restaurants. …

The first column of Table 3 contains the wage rate for a McDonald’s crew member in US dollars (at then-current exchange rates), while the third column contains the price of a Big Mac (again in US dollars). For ease of comparison, the second column expresses the McWage in the economic region indicated relative to its value in the United States. Finally, the fourth column contains the ratio of the price of a Big Mac to the McWage (that is, it contains the measure of Big Macs per hour of work, BMPH).

Page 36:

Table 3: McWages, Big Mac Prices, and Big Macs Per Hour of Work (BMPH), 2007

Countries and Economic Regions

McWage

McWage Ratio

Big Mac Price

BMPH

U.S.

7.33

1

3.04

2.41

Canada

6.8

0.93

3.1

2.19

Russia

2.34

0.32

1.96

1.19

South Africa

1.69

0.23

2.08

0.81

China

0.81

0.11

1.42

0.57

India

0.46

0.06

1.29

0.35

Japan

7.37

1.01

2.39

3.09

The rest of Asia*

1.02

0.14

1.95

0.53

Eastern Europe*

1.81

0.25

2.26

0.8

Western Europe*

9.44

1.29

4.23

2.23

Middle East*

0.98

0.13

2.49

0.39

Latin America*

1.06

0.14

3.05

0.35

* Note: The McWage is the wage of a crew member at McDonald’s. The McWage Ratio is the McWage relative to its US value. BMPH is the McWage divided by the price of a Big Mac. Economic regions are aggregated using population weights from 2010. The rest of Asia includes Hong Kong, Indonesia, Korea, Malaysia, Philippines, Singapore, Sri Lanka, Taiwan, and Thailand; Eastern Europe includes Azerbaijan, Belarus, Czech Republic, Estonia, Georgia, Latvia, Lithuania, Poland and Ukraine; Western Europe includes Austria, Belgium, Denmark, Finland, France, Germany, Ireland, Italy, Netherlands, Norway, Spain, Sweden, Switzerland, and UK; the Middle East includes Egypt, Israel, Lebanon, Morocco, Pakistan, Saudi Arabia, and Turkey; Latin America includes Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Paraguay, and Venezuela.

[130] Report: “The Budget and Economic Outlook: An Update.” Congressional Budget Office, August 2011. <www.cbo.gov>

Page 90: “Labor productivity is average real output per hour of labor. The growth of labor productivity is defined as the growth of real output that is not explained by the growth of labor input alone.”

[131] Textbook: Principles of Macroeconomics (8th edition). By N. Gregory Mankiw. Cengage Learning, 2016.

Page 13:

The differences in living standards around the world are staggering. …

What explains these large differences in living standards among countries and over time? The answer is surprisingly simple. Almost all variation in living standards is attributable to differences in countries’ productivity—that is, the amount of goods and services produced by each unit of labor input. In nations where workers can produce a large quantity of goods and services per hour, most people enjoy a high standard of living; in nations where workers are less productive, most people endure a more meager existence.

[132] Webpage: “Glossary.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed April 25, 2017 at <www.bls.gov>

“Labor productivity refers to the relationship between output and the labor time used in generating that output. It is the ratio of output per hour.”

[133] Webpage: “Labor Productivity and Costs, Frequently Asked Questions.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed April 25, 2017 at <www.bls.gov>

How is productivity defined?

Productivity is a measure of economic efficiency which shows how effectively economic inputs are converted into output.

How is productivity measured by BLS?

Productivity is measured by comparing the amount of goods and services produced with the inputs which were used in production. Labor productivity is the ratio of the output of goods and services to the labor hours devoted to the production of that output.

[134] Speech: “The Outlook for the Economy.” By Janet L. Yellen. At the Providence Chamber of Commerce, Providence, Rhode Island, May 22, 2015. <www.federalreserve.gov>

The Federal Reserve’s objectives of maximum employment and price stability do not, by themselves, ensure a strong pace of economic growth or an improvement in living standards. The most important factor determining living standards is productivity growth, defined as increases in how much can be produced in an hour of work. Over time, sustained increases in productivity are necessary to support rising incomes.

[135] Textbook: Principles of Macroeconomics (8th edition). By N. Gregory Mankiw. Cengage Learning, 2016.

Page 13:

The differences in living standards around the world are staggering. …

What explains these large differences in living standards among countries and over time? The answer is surprisingly simple. Almost all variation in living standards is attributable to differences in countries’ productivity—that is, the amount of goods and services produced by each unit of labor input. In nations where workers can produce a large quantity of goods and services per hour, most people enjoy a high standard of living; in nations where workers are less productive, most people endure a more meager existence.

[136] Report: “The BLS Productivity Measurement Program.” By Edwin R. Dean and Michael J. Harper. U.S. Bureau of Labor Statistics, February 25, 1998. <www.bls.gov>

Page 3:

Using the Accounts, the BLS [1959] introduced annual indexes of real product per man-hour for the total private economy and for the private nonagricultural economy. (Measures for total manufacturing had been introduced in 1955.) The aggregate measures were developed under the supervision of Jerome A. Mark. By this time it was widely recognized that aggregate productivity advances were a necessary condition for rising living standards.

[137] Book: The Age of Diminishing Expectations: U.S. Economic Policy in the 1990s (3rd edition). By Paul Krugman. MIT Press, 1997.

Page 211: “Productivity isn’t everything, but in the long run it is almost everything. A country’s ability to improve its standard of living over time depends almost entirely on its ability to raise its output per worker.”

[138] Article: “What Can Labor Productivity Tell Us About the U.S. Economy? By Shawn Sprague. U.S. Bureau of Labor Statistics, May 2014. <www.bls.gov>

So, why is it important for us to measure labor productivity? Because, over the long run, productivity growth is the economic factor that has the potential to lead to improved living standards for the participants of an economy—in the form of higher consumption of goods and services. With growth in labor productivity, an economy is able to produce increasingly more goods and services for the same amount of work. And, because of this additional production, it is possible for a greater quantity of goods and services to ultimately be consumed for a given amount of work.

[139] Report: “A Productivity Primer.” U.S. Senate Joint Economic Committee, November 7, 2003. <www.jec.senate.gov>

Page 1: “Labor productivity is the most important driver of our standard of living, and its continued rapid growth is great news for the long-run prosperity of the American people.”

[140] Article: “The U.S. Economy to 2016: Slower Growth as Boomers Begin to Retire.” By Betty W. Su. Bureau of Labor Statistics Monthly Labor Review, November 2007. Pages 13–32. <www.bls.gov>

Page 16: “As mentioned earlier, one striking aspect of recent U.S. economic history has been vigorous growth in labor productivity. High productivity growth allows for a mix of higher wages and profits and lower consumer prices. Together, these permit a higher standard of living and quality of life.”

[141] Report: “The 2012 Long-Term Budget Outlook.” Congressional Budget Office, June 2012. <cbo.gov>

Pages 25–26:

Long-term economic growth could differ greatly from the path that underlies the budget projections in this report. CBO assumes that in the long run, total factor productivity will grow by 1.3 percent annually, approximately the average rate seen over the past half century. A small change in the growth of productivity can, over a long period, have a larger effect on GDP than most recessions do. For example, CBO estimates that during the depths of the recessions experienced since the 1970s, GDP was more than 4 percent lower, on average, than it could have been if the nation’s labor force and capital stock had been fully utilized; in addition, output subsequently remained below potential levels for an average of three years. Over the course of a lengthy recession, the cumulative loss in GDP would be substantial, but as long as the economy fully recovered, GDP would return to its previous growth path. By comparison, if productivity growth was 0.3 percentage points lower every year than CBO had assumed, GDP in the 10th year would be 3 percent lower than projected, but cumulative GDP over that decade would be lower by about 16 percent of one year’s output, and that shortfall would be growing at an increasing rate. In other words, the shortfall from a recession is generally temporary, whereas a change in the long-term rate of productivity growth reduces output by an ever-increasing amount.

[142] Report: “What Can Labor Productivity Tell Us About the U.S. Economy.” By Shawn Sprague. U.S. Department of Labor, Bureau of Labor Statistics, Beyond the Numbers, May 2014. <www.bls.gov>

Pages 1–2:

This fact might strike some as surprising: workers in the U.S. business sector worked virtually the same number of hours in 2013 as they had in 1998—approximately 194 billion labor hours. What this means is that there was ultimately no growth at all in the number of hours worked over this 15-year period, despite the fact that the U.S population gained over 40 million people during that time, and despite the fact that there were thousands of new businesses established during that time.

And given this lack of growth in labor hours, it is perhaps even more striking that American businesses still managed to produce 42 percent—or $3.5 trillion—more output in 2013 than they had in 1998, even after adjusting for inflation. One might wonder how such a large amount of additional output came into existence, given that American workers did not put in any more hours of work in this most recent year than they had 15 years earlier. One thing can be said for certain: the entirety of this additional output growth must have come from productive sources other than the number of labor hours. For example, businesses may increase output growth by investing in faster equipment, hiring more high-skilled and experienced workers, and reducing material waste or equipment downtime. In these and other cases, output may be increased without increasing the number of labor hours used. Gains in output such as these are indicative of growth in labor productivity over a period.

[143] Report: “A Productivity Primer.” U.S. Senate Joint Economic Committee, November 7, 2003. <www.jec.senate.gov>

Page 1:

Productivity growth is driven by three factors: investment in equipment, buildings, or other productive resources; increasing worker skills; and innovation. For instance, an accounting firm might see productivity increase (measured in terms of the number of financial reports prepared) if it purchases new high-speed computers for its staff, hires workers with better accounting and computer skills, or invents a new system that allows it to access electronically the day-to-day financial information of its customers.

[144] Report: “What Can Labor Productivity Tell Us About the U.S. Economy.” By Shawn Sprague. U.S. Department of Labor, Bureau of Labor Statistics, Beyond the Numbers, May 2014. <www.bls.gov>

Pages 1–2:

And given this lack of growth in labor hours, it is perhaps even more striking that American businesses still managed to produce 42 percent—or $3.5 trillion—more output in 2013 than they had in 1998, even after adjusting for inflation. One might wonder how such a large amount of additional output came into existence, given that American workers did not put in any more hours of work in this most recent year than they had 15 years earlier. One thing can be said for certain: the entirety of this additional output growth must have come from productive sources other than the number of labor hours. For example, businesses may increase output growth by investing in faster equipment, hiring more high-skilled and experienced workers, and reducing material waste or equipment downtime. In these and other cases, output may be increased without increasing the number of labor hours used. Gains in output such as these are indicative of growth in labor productivity over a period. …

Labor productivity is defined as real output per labor hour, and growth in labor productivity is measured as the change in this ratio over time. Labor productivity growth is what enables workers to produce more goods and services than they otherwise could for a given number of work hours. As an example, suppose workers in a factory can make 20 cars an hour. One month, the company modernizes machinery and the workers take training classes to help improve their performance. Using the new machinery and recently acquired knowledge, the same workers can now make 30 cars an hour—which is a productivity gain of 10 cars per hour, a 50 percent gain. As this example illustrates, there are multiple sources and factors of production that can lead to labor productivity growth. The labor productivity estimate encompasses the overall contribution of all of these factors over a given period.

[145] Working paper: “Economic Growth.” By John H. Cochrane. University of Chicago, Booth School of Business, March 16, 2016. <faculty.chicagobooth.edu>

Page 67:

In turn, productivity comes from new ways of doing things: New ideas, at heart; new inventions, new products, new processes, new technology; new ways of organizing companies; new and better skills among workers. Southwest Airlines figuring out how to turn a plane around in 20 minutes, and Walmart mastering supply logistics, are as much productivity growth as installing scanners or ATMs. Workers who know how to use computers rather than shovels produce a lot more per hour.

[146] Report: “Capacity Utilization and Measurement of Agricultural Productivity.” By James H. Hauver, Jet Yee, and V. Eldon Ball. U.S. Department of Agriculture, August 1991. <naldc.nal.usda.gov>

Page 12:

Productivity growth rates manifest sharp year-to-year volatility, possibly masking trends over time. In order to remove some of the data noise, we computed 5-year moving average productivity growth rates for both adjusted and unadjusted productivity time series. The results are shown in figure 10. Four patterns are evident. First, by using moving averages, much of the volatility of the data is removed.

[147] Webpage: “What are Moving Average or Smoothing Techniques?” National Institute of Standards and Technology, NIST/SEMATECH e-Handbook of Statistical Methods. Accessed April 25, 2017 at <www.itl.nist.gov>

Smoothing data removes random variation and shows trends and cyclic components.

Inherent in the collection of data taken over time is some form of random variation. There exist methods for reducing or canceling the effect due to random variation. An often-used technique in industry is “smoothing”. This technique, when properly applied, reveals more clearly the underlying trend, seasonal and cyclic components.

There are two distinct groups of smoothing methods.

• Averaging Methods

• Exponential Smoothing Methods

[148] Report: “Technical Information About the BLS Major Sector Productivity and Costs Measures.” U.S. Bureau of Labor Statistics, March 11, 2008. <www.bls.gov>

Page 2:

The business sector thereby excludes many activities where it is difficult to draw inferences on productivity from NIPA [National Income and Product Accounts] output measures. Such inferences would be questionable mainly because the output measures are based largely on incomes of input factors. The farm sector, which is subject to unique external forces, also is excluded to yield the nonfarm business sector, the principal focus of many productivity studies.

Page 5:

Short-term movements in productivity and unit labor costs often result from cyclical variation in output, as noted below, and may also reflect unusual events such as drought. These short-term movements are sometimes substantially greater or smaller than long-term averages of productivity and cost movements. For example, productivity growth for 1 or 2 years can be substantially greater than the average for the business cycle that includes these years.

[149] Report: “The BLS Productivity Measurement Program.” By Edwin R. Dean and Michael J. Harper. U.S. Bureau of Labor Statistics, February 25, 1998. <www.bls.gov>

Pages 3–4:

In limiting the measures to the total private sector, BLS [the U.S. Bureau of Labor Statistics] [1959, p. 1] recognized that “there is no satisfactory method of measuring the goods and services provided by the government.” In part, government output in the NIPAs [National Income and Product Accounts] was measured using data on labor inputs, which implies no productivity change.

The aggregate labor productivity measures remain the most frequently cited product of the BLS productivity program. … In addition to general government, the business sector excludes the following items from gross domestic product: private households and nonprofit institutions and the NIPA imputation of the rental value of owner occupied dwellings. Like government, households and institutions are excluded because they are measured with labor inputs. Owner occupied housing is excluded because no corresponding labor hours data are available.

[150] Phone call from Just Facts to an economist at the U.S. Bureau of Labor Statistics, Division of Major Sector Productivity, February 2, 2017.

Summary of the economist’s statements: BLS considers “nonfarm business” is the “most concrete” measure of productivity for the U.S. economy, because it excludes sectors that are volatile or don’t produce traditional output like the farm sector, non-profits, and government.

[151] Calculated with the dataset: “Labor Productivity, Nonfarm Business Sector, All Employed Persons, Percent Change From Previous Year, 1947–2016.” U.S. Bureau of Labor Statistics, February 2, 2017. <www.bls.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[152] Working paper: “Challenges to Mismeasurement Explanations for the U.S. Productivity Slowdown.” By Chad Syverson. National Bureau of Economic Research, February 2016. <www.nber.org>

Page 1: “The United States is experiencing a slowdown in measured labor productivity growth. From 2005 through 2015, labor productivity growth has averaged 1.3% per year. This is down from a trajectory of 2.8% average annual growth sustained over 1995–2004.1

Page 3:

In this study I explore the quantitative plausibility of the mismeasurement hypothesis. One fact dominates the discussion: had the measured productivity slowdown not happened, measured GDP in 2015 would be, conservatively, $2.9 trillion (16%) higher than it is. This is $9,100 for every person or $23,400 for every household in the U.S.

1 Figures are from the nonfarm private business labor productivity series compiled by the U.S. Bureau of Labor Statistics. In this paper I use the series through the end of 2015 to match other available data, but no end to the slowdown is observed in the preliminary productivity numbers for 2016(Q1), which saw annualized labor productivity growth of -0.6%. The post-1995 fast/slow cycle followed on the heels of another much-studied-but-still-debated slowdown. After labor productivity growth averaged 2.7% per year from 1947–1973, it fell to 1.5% per year over 1974–1994.

[153] Book: Productivity Management: A Practical Handbook. By Joseph Prokopenko. International Labour Office, 1987.

Page 242:

Pre-employment education

There are two main goals of pre-employment education: to create productivity awareness and to prepare youth for productive work by teaching the necessary knowledge and skills. Unfortunately, too much attention is paid to developing formal knowledge and too little to practical skills.

For example British industrialists have long been complaining that business and management education in the United Kingdom is oriented towards teaching how to trade and how to invest, rather than how to add new value.

Some prestigious educational institutions place too much emphasis on purely academic matters instead of teaching people how to manage factories and shop-floor production. Too much emphasis is still placed on management sciences and research instead of on preparing creative entrepreneurs capable of innovating, and of organising and managing work. Under such a system, it is quite normal that the most gifted go on to academic studies, and the less gifted are forced to work in industry.

A change of emphasis from a knowledge-based or academic system of education (both secondary and higher) to one based on problem-solving and the completion of concrete tasks would result in an improvement in the productivity culture.

NOTES:

  • For facts about the practical literacy skills of U.S. adults, visit Just Facts’ research on this issue.
  • For facts about practical skill development in U.S. higher education, visit Just Facts’ research on this issue.

[154] Book: Youth Unemployment in the North: Young People on the Labour Market— Actions to Combat Unemployment. Nordic Council Of Ministers, 1987.

Page 190:

General secondary education is oriented towards higher education. As a rule, secondary schools do not equip school leavers with any practical skills that would enable them to get a job. Young people receive a good general education from secondary school but their business and financial skills are mostly insufficient. Moreover, they are not prepared for entering into a competitive labour market.

[155] Report: “Estimated Macroeconomic Impacts of the American Recovery and Reinvestment Act of 2009.” Congressional Budget Office, March 2, 2009. <www.cbo.gov>

Page 2:

In contrast to its positive near-term macroeconomic effects, the legislation will reduce output slightly in the long run, CBO estimates. The principal channel for that effect, which would also arise from other proposals to provide short-term economic stimulus by increasing government spending or reducing revenues, is that the law will result in an increase in government debt. To the extent that people hold their wealth as government bonds rather than in a form that can be used to finance private investment, the increased debt will tend to reduce the stock of productive private capital. In economic parlance, the debt will “crowd out” private investment.

[156] Book: Immigration in America Today: An Encyclopedia. By James Loucky, Jeanne Armstrong, and Lawrence J. Estrada. Greenwood Press, 2006.

Page 308:

The liberalization of immigration policy following the 1965 Immigration and Naturalization Act dramatically changed the immigrant composition in America. … Many post-1965 immigrants were highly educated and trained workers. In the 1970s, 25 percent of immigrants were professionals and often more than 40 percent were white-collar workers. This trend continued into the 1980s. From 1976 to 1990, more than 35 percent of employed immigrants were in professional and other white-collar jobs, and an additional 12 percent were in skilled crafts (Ueda 1998).

This human capital migration was counteracted by a large group of low-skilled workers. Service workers, laborers, and semiskilled operatives composed about 46 percent of employed immigrants in this same time period. The flow of the low-skilled and under-educated immigrants rose in numbers and in percentages in the 1980s and 1990s. Hispanic, Asian, and West Indian workers moved into the service and semi-skilled job markets in large cities like Los Angeles and New York, causing increasing friction and conflict with native black workers (Ueda 1998).

NOTE: For more facts about immigration and economics, visit Just Facts’ research on this issue.

[157] Report: “National Skills Strategy, 14–19, Education.” U.K. House of Commons Education and Skills Committee, Sixth Report of Session 2004–05, Volume II, March 31, 2005. <www.tsoshop.co.uk>

Page 385:

There is a positive correlation between skills and productivity. Lower skills levels are estimated49 to contribute up to 20% of the productivity gap with France and Germany. Numerous international “matched-plant” studies have shown that, whilst other factors are also important, lower levels of skills in the UK workforce led to lower output per employee through:

• lower proportion of workers being qualified specifically to do their current role;

• more machine down-time;

• slower implementation of new technologies and production techniques; and

too much managerial focus on routine tasks.

In terms of benefits to the individual, there is a significant relationship between qualification levels and earnings.50 Higher levels of qualification attract higher earnings, vocational qualifications (VQs) tend to provide lower wage returns than their academic counterparts and some level VQs appear to confer no earnings gain, although higher returns to low level VQs can be found in certain sectors. The construction sector, for example, yields high returns to level 2 VQs.

Analysis of Industry level data on training and productivity51 found that industry productivity levels are significantly higher if more training is undertaken. The study also finds that the overall effect of training on productivity is about twice as high as the wage effect (e.g., raising the proportion of workers trained in an industry by, say, 5 percentage points is associated with a 4% increase in average value added per worker and a 1.6% increase in wages).

Higher productivity does not necessarily imply higher profitability and there is currently very little evidence on the strength of the link between investment in skills and company profit. Attributing improvements in financial performance directly to skills investment is difficult as there are many factors that influence profitability. There is, however, some US evidence52 that, after controlling for other factors, the companies who made above average investment in education and training saw an annualized return of 16.3, compared to a market aver-age of 9.2%53 over a five-year period. The same research concludes that businesses’ treatment of such investment leads to under-investment in skills development.

[158] Report: “Investing in English Skills: The Limited English Proficient Workforce in U.S. Metropolitan Areas.” By Jill H. Wilson. Brookings Institution, September 2014. <www.brookings.edu>

Page 1:

Nearly one in 10 working-age U.S. adults—19.2 million persons aged 16 to 64—is considered limited English proficient. Two-thirds of this population speaks Spanish, but speakers of Asian and Pacific Island languages are most likely to be LEP. The vast majority of working-age LEP adults are immigrants, and those who entered the United States more recently are more likely to be LEP.

Working-age LEP adults earn 25 to 40 percent less than their English proficient counterparts. While less educated overall than English proficient adults, most LEP adults have a high school diploma, and 15 percent hold a college degree. LEP workers concentrate in low-paying jobs and different industries than other workers.

Page 2:

English proficiency is a strong predictor of economic standing among immigrants regardless of educational attainment. Numerous studies have shown that immigrants who are proficient in English earn more than those who lack proficiency, with higher skilled immigrants reaping the greatest advantage.2 Conversely, high-skilled immigrants who are not proficient in English are twice as likely to work in “unskilled” jobs (i.e. those requiring low levels of education or training) as those who are proficient in English.3 This underemployment represents a loss of productivity that yields lower wages for individuals and families and lower tax revenues and consumer spending for local areas. LEP immigrants also have higher rates of unemployment and poverty than their English proficient counterparts.4 Moreover, higher proficiency in English among immigrants is associated with the greater academic and economic success of their children.5 English skills also contribute to immigrants’ civic involvement and social connection to their new home.6

NOTE: For more facts about immigration and economics, visit Just Facts’ research on this issue.

[159] Paper: “Federal Regulation and Aggregate Economic Growth.” By John W. Dawson and John J. Seater. Journal of Economic Growth, January 2013. <link.springer.com>

Pages 30–31:

Regulation’s overall effect on output’s growth rate is negative and substantial. Federal regulations added over the past fifty years have reduced real output growth by about two percentage points on average over the period 1949-2005. That reduction in the growth rate has led to an accumulated reduction in GDP of about $38.8 trillion as of the end of 2011. That is, GDP at the end of 2011 would have been $53.9 trillion instead of $15.1 trillion if regulation had remained at its 1949 level. One channel through which regulation has reduced output is TFP [total factor productivity]. We find that federal regulation can explain much of the famous and famously puzzling productivity slowdown of the 1970s.

Our results are qualitatively consistent with those obtained from studies using the various cross-country and panel data sets on regulation. Quantitatively, our estimated impact of regulation on aggregate output, large as it is, is similar to or lower than the micro-level impacts estimated in the cross-country and panel data studies. The cross-country and panel data are constructed very differently from our data, covering a subset of total regulations but over an array of countries. It thus seems that regulation has strong and robust negative effects on aggregate output.

[160] Book: Conditional Cash Transfers in Latin America. Edited by Michelle Adato and John Hoddinott. Johns Hopkins University Press, 2010.

Chapter 6: “The Economics of Conditional Cash Transfers.” By Jere R. Behrman and Emmanuel Skoufias. Pages 127–158.

Page 136:

The sectors that provide services related to human capital investments may produce inefficiently because regulations preclude efficient production of an efficient basket of commodities. For example, regulations that limit hours during which schools are open, limit textbook choices, impose quality standards based on different conditions in other economies, or limit the provision of services to public providers may result in much greater costs of achieving specific investments than would be possible with fewer regulations.

[161] Book: The Political Process and Economic Change. Edited by Kristen R. Monroe (Professor of Political Science at the University of California, Irvine). Agathon Press, 1983. Chapter 2: “Politics, Economics, and the Underground Economy. By Bruno S. Frey (University of Zurich).

Page 23:

Although an increase in regulation may increase or decrease productivity … recent American research suggests that under present conditions, productivity is negatively affected by government regulations for the following reasons:

1. Government regulations hamper technical progress because an increasing share of expenditures for research and development is siphoned off to meet safety and environmental standards.17 Denison (1979a, b) suggests that the average annual impact of environmental regulations imposed after 1967 on the rate of productivity growth was –0.05% in 1967–1969, –0.1% in 1969–1973, –0.22% in 1973–1975, and –0.08% in 1975–1978. Christainsen and Haveman (1981) have found that federal regulations were responsible for between 12 and 21% of the slowdown in the growth of labor productivity in U.S. manufacturing during 1973–1977 as compared to 1958–1965.

2. Government regulations lead to inefficiencies in sectoral allocations (e.g., see Posner, 1975, or Hamer, 1979).

3. The whole private official economy is strongly burdened. According to a well-known estimate by Weidenbaum (1979), the direct and indirect costs of federal regulations alone in the United States amounted to 3.6% of the gross national product (GNP) in 1976; another estimate (Downing and Lawson, 1979) that included state regulations concluded that the figure was 9.4% of the GNP for the same year. One hastens to add that these studies look only at the costs imposed by government regulations; if the benefit side had also been considered, the overall effect might well have been positive.

The issue of whether government regulations in effect today benefit or hamper productivity in the official private economy is thus unresolved; the answer depends on the specific conditions of the country and the period examined.

[162] Report: “The Sources of Economic Growth in OECD Countries.” Organization for Economic Cooperation and Development, 2003. <www.oecd-ilibrary.org>

Page 95:

This chapter1 extends the analysis of how policy influences growth by exploring industry-level data. In particular, it assesses how different policy and institutional settings in both product and labour markets affect productivity and innovation activity. Aggregate productivity patterns are largely the result of within-industry performance in the OECD countries, and the latter is negatively affected by strict product market regulations, especially if there is a significant technology gap with the technology leader. There is also evidence of an indirect negative effect of strict product market regulations on productivity via their impact on innovation activity. Likewise, by raising labour adjustment costs, strict employment protection legislation tends to hinder productivity, unless these higher costs are offset by lower wages and/or more internal training. However, strict employment protection legislation does not affect innovation activity, but rather tends to tilt sectoral specialisation towards industries where technological enhancement can be accommodated with internal training.

Page 121:

Most prominently, there is evidence that stringent regulatory settings in the product market, as well as strict employment legislation, have a negative bearing on productivity at the industry – and, therefore, macro – levels. However, these policy influences are not straightforward, and depend on a number of factors.

The impact of regulations and institutions on performance varies, depending on the market and technology conditions in which it is operating. In particular, the burden of strict product market regulations on productivity seems to be greater the larger the technological gap with the industry/country leader: strict regulation hinders the adoption of existing technologies, possibly because it reduces competitive pressures or technology spillovers. In addition, strict product market regulations also have a negative impact on the process of innovation itself (insofar as it can be proxied by R&D expenditure). Thus, given the strong impact of R&D on productivity, there is also an indirect channel whereby strict product market regulations may reduce the scope for productivity enhancement.

The link between employment protection legislation and productivity is also complex. There is evidence to suggest that high hiring and firing costs weaken productivity performance, especially when they are not offset by wages and/or internal training, thereby inducing sub-optimal adjustments of the workforce to technology changes and innovation. These considerations are consistent with the firm-level evidence (see Ahn, 2001, for a survey) suggesting that the effects on productivity of innovation and adoption of new technologies are enhanced in firms with a highly-skilled workforce or with strong investment in training.

[163] Article: “Inequality is Central to the Productivity-Pay Gap.” By Lawrence Mishel. Economic Policy Institute, July 29, 2015. <www.epi.org>

The point is to show that the pay of a typical worker has not grown along with productivity in recent decades, even though it did just that in the early post-war period. That is, it shows a substantial disconnect between workers’ pay and overall productivity—a disconnect that has not always existed. We use data on production/nonsupervisory workers because there is no other data series on the pay of a typical worker that goes back to the early post-war period. The point of the chart is to show not only the current divergence but also that it was not always present—also, these data tend to move with the economy-wide median wage.

[164] Statement: “Middle Class Prosperity Project, Forum on Economic Challenges Facing the Middle Class.” By Elizabeth Warren, February 24, 2015. <democrats.oversight.house.gov>

“But starting in the 1980’s, something changed. Productivity and GDP [gross domestic product] just kept going up, but workers were left behind. In the 32 years from 1980 to 2012, 90% of Americans got zero income growth—nothing. All of the income growth in that 32 year period went to those at the top.”

[165] Commentary: “You Deserve a Raise Today. Interest Rates Don’t.” By the Editorial Board. New York Times, September 7, 2015. <www.nytimes.com>

In a healthy economy with upward mobility and a thriving middle class, hourly compensation (wages plus benefits) rises in line with labor productivity. But for the vast majority of workers, pay increases have lagged behind productivity in recent decades. Since the early 1970s, median pay has risen by only 8.7 percent, after adjusting for inflation, while productivity has grown by 72 percent. Since 2000, the gap has become even bigger, with pay up only 1.8 percent, despite productivity growth of 22 percent.

[166] Twitter post: “The Defining Economic Challenge of Our Time.” By Hillary Clinton. July 13, 2015. <twitter.com>

“The defining economic challenge of our time: Raising incomes for everyday Americans. … You’re working harder but your wages aren’t going up … Economic Policy Institute [chart] … Cumulative percent change since 1948 … Productivity [=] 240.4% … Hourly compensation [=] 108.3%”

[167] Article: “Why the Gap Between Worker Pay and Productivity Is So Problematic.” By Gillian B. White. The Atlantic, September 7, 2015. <www.theatlantic.com>

But wage stagnation isn’t just a problem borne of the financial crisis. When you look at the relationship between worker wages and worker productivity, there’s a significant and, many believe, problematic, gap that has arisen in the past several decades. Though productivity (defined as the output of goods and services per hours worked) grew by about 74 percent between 1973 and 2013, compensation for workers grew at a much slower rate of only 9 percent during the same time period, according to data from the Economic Policy Institute.

[168] Commentary: “Productivity and Pay.” By Paul Krugman. New York Times, September 6, 2015. <krugman.blogs.nytimes.com>

The divergence between pay and productivity—a lot of productivity gains, almost total failure to trickle down—is one of the most striking features of American economics these past 40 (!) years. It’s also the subject of endless attempts at debunking, of claims that the divergence is somehow a statistical artifact. What Bivens and Mishel do is take on these arguments carefully, not dismissing them completely, but showing that they explain only a fraction of what we see. Rising benefits are mainly a pre-1979 issue, explaining almost nothing since then; the “terms of trade”—consumer prices rising faster than the prices of U.S. output—is also mostly pre-1979, and in any case only a fractional concern. And so on.

[169] Webpage: “Martin Feldstein.” National Bureau of Economic Research, September 2015. <www.nber.org>

Martin Feldstein is the George F. Baker Professor of Economics at Harvard University and President Emeritus of the National Bureau of Economic Research. He served as President and CEO of the NBER from 1977–82 and 1984–2008. He continues as a Research Associate of the NBER. The NBER is a private, nonprofit research organization that has specialized for nearly 100 years in producing nonpartisan studies of the American economy.

[170] Working paper: “Did Wages Reflect Growth in Productivity?” By Martin Feldstein. National Bureau of Economic Research, April 2008. <www.nber.org>

Page 1:

The level of productivity doubled in the U.S. nonfarm business sector between 1970 and 2006. Wages, or more accurately total compensation per hour, increased at approximately the same annual rate during that period if nominal compensation is adjusted for inflation in the same way as the nominal output measure that is used to calculate productivity.

Page 2:

Two principal measurement mistakes have led some analysts to conclude that the rise in labor income has not kept up with the growth in productivity. The first of these is a focus on wages rather than total compensation. Because of the rise in fringe benefits and other noncash payments, wages have not risen as rapidly as total compensation. It is important therefore to compare the productivity rise with the increase of total compensation rather than with the increase of the narrower measure of just wages and salaries.

The second measurement problem is the way in which nominal output and nominal compensation are converted to real values before making the comparison. Although any consistent deflation of the two series of nominal values will show similar movements of productivity and compensation, it is misleading in this context to use two different deflators, one for measuring productivity and the other for measuring real compensation.

[171] Webpage: “The Productivity–Pay Gap.” Economic Policy Institute. Updated August 2016. <www.epi.org>

Disconnect between productivity and a typical worker’s compensation, 1948–2015

Disconnect Between Productivity and a Typical Worker’s Compensation

Note: Data are for average hourly compensation of production/nonsupervisory workers in the private sector and net productivity of the total economy. “Net productivity” is the growth of output of goods and services minus depreciation per hour worked.

[172] Report: “Workers’ Compensation: Growing Along with Productivity.” By James Sherk. Heritage Foundation, May, 31, 2016. <report.heritage.org>

Productivity and Pay for Different Workers

A major reason why some studies show a gap between pay and productivity is that they compare different groups of employees and ignore a portion of employees’ compensation. These studies measure the productivity of all employees as well as the self-employed. However, they only consider the compensation of some employees: private-sector “production and non-supervisory employees” covered by the Bureau of Labor Statistics (BLS) payroll survey.17

BLS data show that production and non-supervisory jobs constitute about 63 percent of jobs in the overall economy.18 This category excludes all government employees, the self-employed, and about 20 percent of private-sector firms’ employees. Among the excluded are the majority of the most highly paid workers in America. This makes a large difference: Over the past generation, compensation has risen faster among high earners than in the rest of the economy.

17 The payroll survey measures only wages; it does not include benefits. The Economic Policy Institute imputes benefits to the payroll-survey based wages using data from the National Income and Product Accounts. See Appendix A for details on this imputation and mathematical mistakes that EPI makes in doing so.

18 The Bureau of Labor Statistics payroll survey reported 96.8 million production and non-supervisory employees in the private sector in 2014. The BLS household survey reported 146.6 million workers in the total economy. These figures include government employees, the self-employed, private household workers, and farm employees. The payroll survey counts America’s 7.1 million multiple job holders separately at each payroll job they hold, while the household survey counts each employee once, no matter how many jobs he holds. To maintain comparability between the surveys, it is necessary to count multiple job holders in the household survey on the same basis as the payroll survey. This yields 153.7 million jobs in the overall economy, of which 63 percent are production and non-supervisory positions covered by the payroll survey.

[173] Working paper: “Did Wages Reflect Growth in Productivity?” By Martin Feldstein. National Bureau of Economic Research, April 2008. <www.nber.org>

Page 2:

Two principal measurement mistakes have led some analysts to conclude that the rise in labor income has not kept up with the growth in productivity. The first of these is a focus on wages rather than total compensation. Because of the rise in fringe benefits and other noncash payments, wages have not risen as rapidly as total compensation. It is important therefore to compare the productivity rise with the increase of total compensation rather than with the increase of the narrower measure of just wages and salaries.

[174] Article: “Comparing the Consumer Price Index with the Gross Domestic Product Price Index and Gross Domestic Product Implicit Price Deflator.” By Jonathon D. Church. U.S. Bureau of Labor Statistics Monthly Labor Review, March 2016. <www.bls.gov>

The Consumer Price Index (CPI) and the gross domestic product (GDP) price index and implicit price deflator are measures of inflation in the U.S. economy. The CPI measures price changes in goods and services purchased out of pocket by urban consumers, whereas the GDP price index and implicit price deflator measure price changes in goods and services purchased by consumers, businesses, government, and foreigners, but not importers. Thus, which one to use in a given scenario depends on one’s purpose.

Inflation can be defined as a consistent increase in an economy’s “price level,” or the price component of total expenditures on a set of goods and services, over a given period. The Consumer Price Index (CPI), a product of the Bureau of Labor Statistics (BLS), is perhaps the most widely used measure of inflation in the United States. The CPI measures the average change over time in the prices paid by urban consumers in the United States for a market basket of goods and services.

The Personal Consumption Expenditures (PCE) price index, produced by the U.S. Bureau of Economic Analysis (BEA), is another measure of consumer inflation and is followed closely by the U.S. Board of Governors of the Federal Reserve System (the Federal Reserve). Despite differences in scope, weight, and methodology, the CPI and the PCE price index both measure inflation from the perspective of the consumer. However, one might be interested in an index that measures price change across a broader or narrower range of goods and services—for example, an index that measures price change across a set of goods and services that includes not just consumer goods and services, but also goods and services purchased by businesses, government, and other entities.

One such measure is the price index associated with the nation’s gross domestic product (GDP). Each quarter, BEA releases data on the level of, and change in, GDP. These data include a breakdown of GDP into price and quantity indexes, as well as a GDP implicit price deflator. The GDP price index and implicit price deflator are derived from the measurement of GDP, giving rise to three main issues that distinguish the GDP price indexes from other measures of inflation. The first issue is the scope of goods and services for which prices are collected and indexes are calculated. The second is the weight attached to prices for these goods and services. The third is the methodological details of price index calculation.

[175] Working Paper: “Did Wages Reflect Growth in Productivity?” By Martin Feldstein. National Bureau of Economic Research, April 2008. <www.nber.org>

Pages 2-3:

The second measurement problem is the way in which nominal output and nominal compensation are converted to real values before making the comparison. Although any consistent deflation of the two series of nominal values will show similar movements of productivity and compensation, it is misleading in this context to use two different deflators, one for measuring productivity and the other for measuring real compensation.

A quick review of what economic theory says about the relation between productivity and compensation will clarify the correct choice of price deflator for making this comparison and will also indicate how productivity and compensation would be expected to move in a competitive economy. In the classroom we often abstract from differences in prices by assuming an economy with a single product and therefore summarize the basic wage determination condition by saying that a competitive firm pays a wage equal to the marginal product of labor. But when we recognize the multiproduct nature of the economy, we say that the competitive firm pays a nominal wage equal to the marginal revenue product of labor, i.e., to the marginal product of labor multiplied by the price of the firm’s product. The key real relation must therefore be between changes in productivity in the nonfarm business sector and changes in the nominal compensation paid in that sector deflated by the product price and not by some consumer price that also reflects goods and services produced outside the domestic nonfarm business sector.

Pages 4–5:

There are of course other questions for which using compensation deflated by the CPI or some other consumer price index is appropriate, including measuring changes in the standard of living of wage earners and in the incentive to supply labor. But the nominal compensation deflated by the CPI is not appropriate for evaluating the relation between productivity and compensation.

Page 8: “In summary, basic theory reminds us that real compensation should be

measured using the same price index that is used to calculate productivity.”

[176] Email from the U.S. Bureau of Economic Analysis to Just Facts, February 21, 2017.

Regarding the correct price index to use when comparing output and compensation, for some questions the same index should be used for both. For example, if one is interested in whether workers’ earnings are rising with productivity gains, then it is appropriate to use the same index for both. Note that this is the same comparing compensation and output in nominal terms.

[177] Article: “The Growing Gap Between Real Wages and Labor Productivity.” By Robert Lawrence. Peterson Institute for International Economics, July 21, 2015. <piie.com>

When appropriately measured, from 1970 to 2000, and perhaps to as late as 2008, the growth in overall worker compensation was precisely as rapid as the growth in average labor productivity would imply. This suggests that the key to explaining sluggish long-run wage growth is understanding productivity growth rather than what drives the distribution of income between capital and labor. If there is something about the American economy that has kept workers from maintaining their share in output as the economy expands, this phenomenon has materialized only relatively recently.

First, production and nonsupervisory workers do not constitute the full US labor force. Broader measures that include the wages of all workers show considerably more real wage growth—a reflection of the fact that the wages of more skilled and educated workers grew much more rapidly than blue-collar workers with less education.

[178] Article: “The Compensation-Productivity Gap: A Visual Essay.” By Susan Fleck, John Glaser, and Shawn Sprague. U.S. Bureau of Labor Statistics Monthly Labor Review, January, 2011. <www.bls.gov>

Page 57:

This visual essay presents real hourly compensation data based on compensation data from the National Income and Product Accounts, which is the same source that the BLS productivity program uses for output. Compensation data are adjusted by using a consumer price index, and output is adjusted by using an implicit price deflator. …

… Because real hourly compensation and labor productivity, which is output per hour, both include hours worked in their calculations, changes in hours worked have no impact on the gap.

Page 62:

A price index measures the price of a basket of goods and services over time. The Compensation-Productivity gap is partly accounted for by the difference between the two price indexes used to remove the effect of inflation. The implicit price deflator, used to remove the effect of inflation on output, measures price changes in the goods and services produced in the nonfarm business sector. The Consumer Price Index measures price changes in the basket of goods and services purchased by families and workers; it is used to calculate real hourly compensation.

[179] Webpage: “Bureau of Economic Analysis, Glossary, I.” U.S. Department of Commerce, Bureau of Economic Analysis. Last updated November 29, 2016. <www.bea.gov>

Implicit price deflator (IPD). The ratio of the current-dollar value of a series, such as gross domestic product (GDP), to its corresponding chained-dollar value, multiplied by 100.”

[180] Article: “Comparing the Consumer Price Index with the Gross Domestic Product Price Index and Gross Domestic Product Implicit Price Deflator.” By Jonathon D. Church. U.S. Bureau of Labor Statistics Monthly Labor Review, March 2016. <www.bls.gov>

The Consumer Price Index (CPI) and the gross domestic product (GDP) price index and implicit price deflator are measures of inflation in the U.S. economy. The CPI measures price changes in goods and services purchased out of pocket by urban consumers, whereas the GDP price index and implicit price deflator measure price changes in goods and services purchased by consumers, businesses, government, and foreigners, but not importers. Thus, which one to use in a given scenario depends on one’s purpose. …

One such measure is the price index associated with the nation’s gross domestic product (GDP). Each quarter, BEA releases data on the level of, and change in, GDP. These data include a breakdown of GDP into price and quantity indexes, as well as a GDP implicit price deflator. The GDP price index and implicit price deflator are derived from the measurement of GDP, giving rise to three main issues that distinguish the GDP price indexes from other measures of inflation. The first issue is the scope of goods and services for which prices are collected and indexes are calculated. The second is the weight attached to prices for these goods and services. The third is the methodological details of price index calculation.

[181] Webpage: “Frequently Asked Questions.” U.S. Department of Labor, Bureau of Labor Statistics. Last updated February 1, 2017. <www.bls.gov>

What is the CPI?

The Consumer Price Index (CPI) is a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services.

How is the CPI used?

The CPI affects nearly all Americans because of the many ways it is used. Following are major uses:

• As an economic indicator.

• As a deflator of other economic series.

• As a means of adjusting dollar values.

[182] Webpage: “Addendum to Frequently Asked Questions.” U.S. Department of Labor, Bureau of Labor Statistics. Last updated March 2, 2011. <www.bls.gov>

The CPI is the most widely used measure of inflation and is sometimes viewed as an indicator of the effectiveness of government economic policy. It provides information about price changes in the Nation’s economy to government, business, labor, and private citizens and is used by them as a guide to making economic decisions. In addition, the President, Congress, and the Federal Reserve Board use trends in the CPI to aid in formulating fiscal and monetary policies.

The CPI and its components are used to adjust other economic series for price changes and to translate these series into inflation-free dollars. Examples of series adjusted by the CPI include retail sales, hourly and weekly earnings, and components of the National Income and Product Accounts.

An interesting example is the use of the CPI as a deflator of the value of the consumer’s dollar to find its purchasing power. The purchasing power of the consumer’s dollar measures the change in the value to the consumer of goods and services that a dollar will buy at different dates. In other words, as prices increase, the purchasing power of the consumer’s dollar declines.

The CPI is often used to adjust consumers’ income payments (for example, Social Security) to adjust income eligibility levels for government assistance and to automatically provide cost-of-living wage adjustments to millions of American workers. As a result of statutory action the CPI affects the income of millions of Americans. Over 50 million Social Security beneficiaries, and military and Federal Civil Service retirees, have cost-of-living adjustments tied to the CPI. In addition, eligibility criteria for millions of food stamp recipients, and children who eat lunch at school, are affected by changes in the CPI. Many collective bargaining agreements also tie wage increases to the CPI.

Another example of how dollar values may be adjusted is the use of the CPI to adjust the Federal income tax structure. These adjustments prevent inflation-induced increases in tax rates, an effect called bracket creep.

[183] Article: “Comparing the Consumer Price Index with the Gross Domestic Product Price Index and Gross Domestic Product Implicit Price Deflator.” By Jonathon D. Church. U.S. Bureau of Labor Statistics Monthly Labor Review, March 2016. <www.bls.gov>

The Consumer Price Index (CPI) and the gross domestic product (GDP) price index and implicit price deflator are measures of inflation in the U.S. economy. The CPI measures price changes in goods and services purchased out of pocket by urban consumers, whereas the GDP price index and implicit price deflator measure price changes in goods and services purchased by consumers, businesses, government, and foreigners, but not importers. Thus, which one to use in a given scenario depends on one’s purpose.

[184] Calculated with data from:

a) Dataset: “Net Multifactor Productivity and Cost, Private Business Sector, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics, March 21, 2018. <www.bls.gov>

Tab: “PG: Private Business Sector (Excluding Government Enterprises)”

Table 2.1: “Analytic Ratios, Levels”

Table 2.2: “Analytic Ratios, Indexes = 100.000, Base Year = 2009”

b) Dataset: “CPI—All Urban Consumers (Current Series).” U.S. Department of Labor, Bureau of Labor Statistics. Accessed January 28, 2018 at <www.bls.gov>

Series: “CUUR0000SA0. All Items in U.S. City Average, All Urban Consumers, Not Seasonally Adjusted, 1982–84=100”

NOTE: An Excel file containing the data and calculations is available upon request.

[185] Calculated with the dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “3. Number of Households, Average Income, and Shares of Income for All Households, by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[186] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[187] Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “3. Number of Households, Average Income, and Shares of Income for All Households, by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[188] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 6:

For this analysis, federal taxes include individual income taxes, payroll taxes, corporate income taxes, and excise taxes, which together accounted for 93 percent of all federal revenues in fiscal year 2013. Revenues from states’ deposits for unemployment insurance, estate and gift taxes, miscellaneous fees and fines, and net income earned by the Federal Reserve, which make up the remaining 7 percent, are not allocated to households in this analysis, mainly because it is uncertain how to attribute those revenues to particular households.

Page 11: “Because of the complexity of estimating state and local taxes for individual households, this report considers federal taxes only. Researchers differ about whether state and local taxes are, on net, regressive, proportional, or slightly progressive, but most agree that state and local taxes are less progressive than federal taxes.”

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[189] Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “3. Number of Households, Average Income, and Shares of Income for All Households, by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[190] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 6:

For this analysis, federal taxes include individual income taxes, payroll taxes, corporate income taxes, and excise taxes, which together accounted for 93 percent of all federal revenues in fiscal year 2013. Revenues from states’ deposits for unemployment insurance, estate and gift taxes, miscellaneous fees and fines, and net income earned by the Federal Reserve, which make up the remaining 7 percent, are not allocated to households in this analysis, mainly because it is uncertain how to attribute those revenues to particular households.

Page 11: “Because of the complexity of estimating state and local taxes for individual households, this report considers federal taxes only. Researchers differ about whether state and local taxes are, on net, regressive, proportional, or slightly progressive, but most agree that state and local taxes are less progressive than federal taxes.”

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[191] Webpage: “Poverty: Measuring Inequality.” World Bank. Accessed April 26, 2017 at <go.worldbank.org>

Gini-coefficient of inequality: This is the most commonly used measure of inequality. The coefficient varies between 0, which reflects complete equality and 1, which indicates complete inequality (one person has all the income or consumption, all others have none). Graphically, the Gini coefficient can be easily represented by the area between the Lorenz curve and the line of equality.

[192] Book: Economic Inequality and Poverty. Edited by Lars Osberg. M.E. Sharpe, 1991.

Page 101: “Where wealth data for representative samples are available, the most common measure is the Gini coefficient.”

[193] Article: “Income Inequality Measures.” By Fernando G. De Maio. Journal of Epidemiology & Community Health, October 2007. <www.ncbi.nlm.nih.gov>

Abstract:

The Gini coefficient has been the most popular method for operationalising income inequality in the public health literature. However, a number of alternative methods exist, and they offer researchers the means to develop a more nuanced understanding of the distribution of income. Income inequality measures such as the generalised entropy index and the Atkinson index offer the ability to examine the effects of inequalities in different areas of the income spectrum, enabling more meaningful quantitative assessments of qualitatively different inequalities. This glossary provides a conceptual introduction to these and other income inequality measures.

[194] Article: “Lower Wages for Whites, Higher Wages for Immigrants, and Inequality for All.” By Jeff Guo. Washington Post, September 16, 2015. <www.washingtonpost.com>

“Between 2013–2014, there was also was no significant improvement on any of the measures of inequality. The gulf between high earners and low earners remains the widest it’s been since at least 1993, the earliest year for which there is comparable data.”

[195] Article: “Median Income Falls For 5th Year, Inequality at Record High.” By Mark Gongloff. Huffington Post, September 17, 2013. <www.huffingtonpost.com>

While median income has fallen, the incomes of top earners have continued to rise, making income inequality worse. The Census Bureau’s measure of inequality, known as the “Gini index,” held steady at 0.477 in 2012, but at the record high set in 2011. A Gini index of 0 means perfect income equality, an index of 1 means one person would get all of the nation’s income. We’re slowly grinding our way towards 1.

[196] Article: “Seeking New Tools to Address a Wage Gap.” By Eduardo Porter. New York Times, November 4, 2014. <www.nytimes.com>

Reducing inequity is hard. Last year the nonpartisan Congressional Budget Office took a look at the history of government efforts to temper rising income inequality over the last three decades. It didn’t find much improvement.

In 1979, government taxes and transfers shrank the Gini index, a measure of income inequality, to 0.358 from 0.476—about the same as cutting inequality to the level prevalent in a more egalitarian European nation like Spain from the level prevalent today in a highly unequal Latin American country like Chile.

American inequality has increased significantly over the intervening decades. But the government does roughly the same job today. In 2010 taxes and transfers reduced the Gini measure to 0.434 from 0.586.

[197] Paper: “Measures of Income Inequality Are Biased or Misinterpreted.” By Ivan Kitov. Social Science Research Network, December 10, 2014. <papers.ssrn.com>

Page 1: “The changing composition of households in the U.S. is the effect explaining the reported increase in Gini coefficient for households since 1967. When corrected for actual decrease in the average household size the relevant Gini coefficient returns to that of personal incomes.”

Page 6:

In Figure 7a, we present the Gini coefficient for households. We intentionally normalized the ratio to its maximum value (0.477 in 2011) in order to show that this inequality measure has risen by 20% since 1967. This dramatic increase is interpreted as a big problem for the US but contradicts the observation of constant Gini coefficient for individuals. Unlike personal incomes, the household data are collected for entities which can evolve in size. … Actually, the fall in the average size is quite spectacular: from 3.2 in 1967 to 2.49 in 2011. The simplest effect leading to the observed size decrease is household split—instead of one big household two smaller households appear. Obviously, the Gini coefficient depends on the distribution of household sizes. For fixed total income, the increasing number of households (split), which share the same amount of money, should result in a higher Gini coefficient. When all households are split to the smallest pieces (one person households) we have the personal income distribution with a larger Gini.

Page 7:

Overall, the Gini coefficient for households has not been changing as the CB [Census Bureau] estimate says because these estimates do not take into account the change in the household size distribution. This is a methodological error. The same logic must be applied to family income distribution—the CB’s estimate is also biased. The mean and median income estimates are also affected by this mistaken procedure. Since the size of household has been decreasing the number of households has been growing faster than the total household population. The mean household income must also be corrected for the changing size. Figure 9a shows the actual evolution of the mean income (the evolution of median income is harder to recover).

[198] Calculated with the dataset: “HH-1. Households by Type: 1940 to Present.” U.S. Census Bureau, November 2016. <www2.census.gov>

“Total households … 2016 [=] 125,819 … 1940 [=] 39,949”

CALCULATION: (125,819 households in 2016 – 39,949 households in 1940) / 39,949 households in 1940 = 260%

[199] Calculated with the dataset: “Table 7.1. Selected Per Capita Product and Income Series in Current and Chained Dollars.” U.S. Department of Commerce, Bureau of Economic Analysis. Last revised January 27, 2017. <www.bea.gov>

“Population … 2016 [=] 323,391,000 … 1940 [=] 132,122,000”

CALCULATION: (323,391,000 population in 2016 – 132,122,000 population in 1940) / 132,122,000 population in 1940 = 145%

[200] Calculated with the dataset: “HH-1. Households by Type, 1940 to Present.” U.S. Census Bureau, November 2016. <www.census.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[201] Calculated with data from:

a) Dataset: “Table H-4. Gini Ratios for Households, by Race and Hispanic Origin of Householder.” U.S. Census Bureau. Accessed May 10, 2015 at <www.census.gov>

“All races”

b) Paper: “The Dynamics of Personal Income Distribution and Inequality in the United States.” By Ivan O. Kitov and Oleg I. Kitov. Society for the Study of Economic Inequality, August 6, 2013. <www.ecineq.org>

NOTES:

  • Ivan Kitov sent the Gini coefficient data for this paper to Just Facts on May 12, 2015. These Gini coefficients were calculated by the authors based on Census Bureau “Consumer Income Reports” dating back to 1946, which are available at https://www.census.gov/prod/www/population.html#p60.
  • The Census Bureau has calculated the Gini index for persons from 1994 to 2013. For the years of overlap with the Kitov calculations, the latter are slightly higher but display the same trends as the Census calculations from year to year. Just Facts queried Ivan Kitov about these minor differences, and he replied that they “might be caused by some differences in the approximation of distribution and information on the highest incomes, which is not published by the CB [Census Bureau].” This is detailed in Kitov’s paper: “Estimates of Income Inequality are Biased or Misinterpreted.” Social Science Research Network, December 10, 2014. https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2536325_code589222.pdf?abstractid=2536325&mirid=1
  • An Excel file containing the data and calculations is available upon request.

[202] Report: “Income and Poverty in the United States: 2015 (Current Population Reports).” By Bernadette D. Proctor, Jessica L. Semega, and Melissa A. Kollar. U.S. Census Bureau, September 2016. <www.census.gov>

Page 3: “The income and poverty estimates shown in this report are based solely on money income before taxes and do not include the value of noncash benefits, such as those provided by the Supplemental Nutrition Assistance Program (SNAP), Medicare, Medicaid, public housing, or employer-provided fringe benefits.”

Page 21:

Data on income collected in the ASEC by the U.S. Census Bureau cover money income received (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, Medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive noncash benefits, such as Supplemental Nutrition Assistance/ food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents, which often take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc. Data users should consider these elements when comparing income levels.

[203] Webpage: “Historical Income Tables: Experimental Measures.” U.S. Census Bureau. Last revised March 10, 2016. <www.census.gov>

Definitions of Alternative Measures of Income: “Table RDI-5. Index of Income Concentration (Gini Index) by Definition of Income.”

[204] Webpage: “Alternative Measures of Income Definitions.” U.S. Census Bureau. Last revised May 11, 2016. <www.census.gov>

Alternative Measures of Income Definitions

The 15 definitions of income shown below are included in the Census Bureau’s “Alternative Measures of Income”:

1. Money income excluding capital gains before taxes. This is the official definition used in Census Bureau reports.

a. Money income after taxes (without earned income credit (EIC)). This is definition 1 minus federal and state income taxes exclusive of the EIC, minus payroll taxes, plus capital gains, and minus capital losses.1

b. Money income after taxes (including EIC). This is definition 1a plus the federal and state EIC. (See definition 7.)

2. Definition 1 less government cash transfers. Government cash transfers include nonmeans-tested transfers such as social security payments, unemployment compensation, and government educational assistance (e.g., Pell Grants), as well as means-tested transfers such as aid to families with dependent children (AFDC, ADC), temporary assistance to needy families (TANF), and supplemental security income (SSI). (For a complete listing of transfer income, see definitions 9 and 12.)

3. Definition 2 plus capital gains. Realized capital gains and losses are simulated as part of the Census Bureau’s federal individual income tax estimation procedure.

4. Definition 3 plus imputed health insurance supplements to wage or salary income. Employer-paid health insurance coverage is treated as part of total worker compensation.

5. Definition 4 less payroll taxes. Payroll taxes are payments for social security old age, survivors, and disability insurance, and for hospital insurance (Medicare).

6. Definition 5 less federal income taxes. Definition 7 shows the effect of the earned income credit (targeted to low-income workers) separately.

7. Definition 6 plus the earned income credit. Includes federal EIC and EIC for nine states (Iowa, Kansas, Massachusetts, Maryland, New York, Oregon, Rhode Island, Vermont, and Wisconsin) that use federal eligibility rules to compute the state credit as a percentage of the federal EIC.

8. Definition 7 less state income taxes.

9. Definition 8 plus nonmeans-tested government cash transfers. Nonmeans-tested government cash transfers include social security payments, unemployment compensation, workers’ compensation, nonmeans-tested veterans’ payments, U.S. railroad retirement, Black lung payments, Pell Grants, and other government educational assistance. (Pell Grants are income-tested but are included here because they are very different from the assistance programs included in the means-tested category.)

10. Definition 9 plus the value of Medicare. Medicare is counted at its fungible value.2

11. Definition 10 plus the value of regular-price school lunches.

12. Definition 11 plus means-tested government cash transfers. Means-tested government cash transfers include AFDC, ADC, TANF, SSI, other public assistance programs, and means-tested veterans’ payments.

13. Definition 12 plus the value of Medicaid. This definition counts Medicaid at its fungible value.

14. Definition 13 plus the value of other means-tested government noncash transfers, including food stamps, rent subsidies, and free and reduced-price school lunches.

a. Definition 14 less medical programs. This is cash income plus all noncash income except imputed income from own home, minus the fungible values of Medicaid and Medicare.

15. Definition 14 plus net imputed return on equity in one’s own home. This definition includes the estimated annual benefit of converting one’s home equity into an annuity, net of property taxes.

Footnotes:

1 Data on capital gains or losses are net gains or losses from sales of capital assets as reported to the Internal Revenue Service on Schedule D.

2 The fungible approach for valuing medical coverage assigns income to the extent that having the insurance would free up resources that would have been spent on medical care. The estimated fungible value depends on family income, the cost of food and housing needs, and the market value of the medical benefits. If family income is not sufficient to cover the family’s basic food and housing requirements, the fungible value methodology treats Medicare and Medicaid as having no income value. If family income exceeds the cost of food and housing requirements, the fungible value of Medicare and Medicaid is equal to the amount which exceeds the value assigned for food and housing requirements (up to the amount of the market value of an equivalent insurance policy (total cost divided by the number of participants in each risk class).

[205] Calculated with the dataset: “Table RDI-5. Index of Income Concentration (Gini Index) by Definition of Income, 1979 to 2003.” U.S. Census Bureau. Accessed April 18, 2017 at <www2.census.gov>

Definitions: “1. Money income excluding capital gains (current measure)” and “15. Definition 14 plus net imputed return on equity in own home.”

NOTE: An Excel file containing the data and calculations is available upon request.

[206] Article: “Donald Trump’s 2016 Republican National Convention Speech.” ABC News, July 22, 2016. <abcnews.go.com>

“Household incomes are down more than $4,000 since the year 2000, that’s 16 years ago.”

[207] Article: “Fact-Checking the Truth That Donald Trump Promised.” By Michael D. Shear and Nick Corasaniti. New York Times, July 21, 2016. <www.nytimes.com>

“Household incomes are down more than $4,000 since the year 2000.”

Fact Check: This is mostly true. Median household income in 2000 was $57,724; in 2014, which has the most recent available data, it was $53,657.

[208] Article: Fact Check: Donald Trump’s Republican Convention Speech, Annotated.” NPR WNYC Radio, July 21, 2016. <www.npr.org>

Household incomes are down more than $4,000 since the year 2000. That’s sixteen years ago.

[That’s true, using median household income data, though he is not measuring from the start of the Obama administration as he is for the other stats here. If he measured from 2008, the drop was $1,656. Measuring from 2000 means measuring from the figure’s near-peak. … Danielle Kurtzleben]

[209] Article: “Fact Check: Donald Trump’s Speech at the Republican National Convention. Vox, July 22, 2016. <www.vox.com>

Trump says: “Household incomes are down more than $4,000 since the year 2000.”

In fact: In 2014, the real median household income was $53,657, according to the Census Bureau. In 2000, it was $57,724, after adjusting for inflation. It has indeed declined by more than $4,000 in real terms. – Dylan Matthews

NOTE: Vox links to the Federal Reserve Bank of St. Louis to support the $57,724 figure. The Federal Reserve Bank of St. Louis, in turn. cites the “U.S. Bureau of the Census” as its source for this data.

[210] Report: “Income and Poverty in the United States: 2014 (Current Population Reports).” By Carmen DeNavas-Walt and Bernadette D. Proctor. U.S. Census Bureau, September 2015. <www.census.gov>

Page 4: “The income and poverty estimates shown in this report are based solely on money income before taxes and do not include the value of noncash benefits, such as those provided by the Supplemental Nutrition Assistance Program (SNAP), Medicare, Medicaid, public housing, or employer-provided fringe benefits.”

Page 21:

Data on income collected in the ASEC by the Census Bureau cover money income received (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, Medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive noncash benefits, such as Supplemental Nutrition Assistance/food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents, which often take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc. Data users should consider these elements when comparing income levels. Moreover, readers should be aware that for many different reasons there is a tendency in household surveys for respondents to underreport their income.

[211] Report: “Income and Poverty in the United States: 2014 (Current Population Reports).” By Carmen DeNavas-Walt and Bernadette D. Proctor. U.S. Census Bureau, September 2015. <www.census.gov>

Page 21: “Data on income collected in the ASEC by the Census Bureau cover money income received (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, Medicare deductions, etc.”

[212] Report: “Income and Poverty in the United States: 2014 (Current Population Reports).” By Carmen DeNavas-Walt and Bernadette D. Proctor. U.S. Census Bureau, September 2015. <www.census.gov>

Page 1: “ ‘Real’ refers to income after adjusting for inflation. All income values are adjusted to reflect 2014 dollars. The adjustment is based on percentage changes in prices between 2014 and earlier years and is computed by dividing the annual average Consumer Price Index Research Series (CPI-U-RS) for 2014 by the annual average for earlier years.”

[213] Calculated with data from:

a) Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

“Table 6. Sources of Income for All Households, by Before-Tax Income Group, 1979 to 2013”

b) Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 27: “Capital Income Excluding Capital Gains [=] Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital. … Other income [=] Income received in retirement for past services or from other sources. … Government transfers … Cash [=] Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.”

c) Webpage: “Current Population Survey (CPS)—Subject Definitions.” United States Census Bureau. Last revised August 25, 2015. <www.census.gov>

“Income Measurement … For each person in the sample 15 years old and over, the CPS asks questions on the amount of money income received in the preceding calendar year from each of the following sources: 1. Earnings 2. Unemployment compensation 3. Workers’ compensation 4. Social security 5. Supplemental security income 6. Public assistance 7. Veterans’ payments 8. Survivor benefits 9. Disability benefits 10. Pension or retirement income 11. Interest 12. Dividends 13. Rents, royalties, and estates and trusts 14. Educational assistance 15. Alimony 16. Child support 17. Financial assistance from outside of the household 18. Other income.”

NOTE: An Excel file containing the data and calculations is available upon request.

[214] Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

“Table 5. Median Household Income, 1979 to 2013 … Before-Tax Income … 2000 [=] $74,300 … 2013 [=] $79,200”

CALCULATION: $79,200 – $74,300 = $4,900

[215] Report: “The Distribution of Household Income and Federal Taxes, 2013.” By Congressional Budget Office, June 2016. <www.cbo.gov>

Page 2: “Household income over time is adjusted for inflation using the price index for personal consumption expenditures as calculated by the Bureau of Economic Analysis.”

[216] Report: “The Distribution of Household Income and Federal Taxes, 2008 and 2009.” Congressional Budget Office, July 10, 2012. <www.cbo.gov>

Page 21:

In this report, CBO adjusted household income for the effects of inflation using the personal consumption expenditures price index. That index is constructed by the Bureau of Economic Analysis as part of the national income and product accounts. Previously, CBO had used the Bureau of Labor Statistics’ research series of the consumer price index for all urban consumers (CPI-U-RS). The average annual inflation rate over the 1979–2009 period was about 0.2 percentage points lower as measured by the PCE price index than as measured by the CPI-U-RS. In CBO’s judgment, the PCE price index is a more appropriate deflator for the measures of income used in this report because its scope includes health care services purchased by third parties on behalf of people (services that are included in the measures of income used in this report) and because it more fully accounts for the adjustments that consumers make to their spending patterns as some prices change relative to other prices.

[217] Calculated with data from:

a) Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Table 5: “Median Household Income, 1979 to 2013”

b) “CPI Detailed Report Data for December 2015.” U.S. Department of Labor, Bureau of Labor Statistics, January 27, 2016. <www.bls.gov>

“Table 24. Historical Consumer Price Index for All Urban Consumers (CPI-U): U. S. city average, all items (1982–84=100, unless otherwise noted)”

c) Dataset: “Table 2.3.4. Price Indexes for Personal Consumption Expenditures by Major Type of Product, Seasonally Adjusted.” U.S. Department of Commerce, Bureau of Economic Analysis. Last revised June 28, 2016. <www.bea.gov>

Line 1: “Personal consumption expenditures (PCE)”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[218] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 2: “In 2013, according to the Congressional Budget Office’s estimates, average household market income—a comprehensive income measure that consists of labor income, business income, capital income (including capital gains), and retirement income—was approximately $86,000.”

Page 6:

For this analysis, federal taxes include individual income taxes, payroll taxes, corporate income taxes, and excise taxes, which together accounted for 93 percent of all federal revenues in fiscal year 2013. Revenues from states’ deposits for unemployment insurance, estate and gift taxes, miscellaneous fees and fines, and net income earned by the Federal Reserve, which make up the remaining 7 percent, are not allocated to households in this analysis, mainly because it is uncertain how to attribute those revenues to particular households.

Page 11: “Because of the complexity of estimating state and local taxes for individual households, this report considers federal taxes only. Researchers differ about whether state and local taxes are, on net, regressive, proportional, or slightly progressive, but most agree that state and local taxes are less progressive than federal taxes.”

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[219] Article: “Warren: The Average Family in the Bottom 90 Percent Made More Money 30 Years Ago.” PolitiFact, January 13, 2015. <www.politifact.com>

Warren, a former law professor and expert on the economic challenges of the middle class, cited a number of statistics to support her point, including: “Well, since 1980, guess how much of the growth in income over the last 32 years—how much of the growth in income did the 90 percent get? Zero. None. Nothing. In fact, it is worse than that. The average family not in the top 10 percent makes less money today than they were making a generation ago.” …

We rate Warren’s claim Mostly True.

[220] Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “3. Number of Households, Average Income, and Shares of Income for All Households, by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[221] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 2: “In 2013, according to the Congressional Budget Office’s estimates, average household market income—a comprehensive income measure that consists of labor income, business income, capital income (including capital gains), and retirement income—was approximately $86,000.”

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[222] Article: “U.S. Income Inequality, on Rise for Decades, Is Now Highest Since 1928.” By Drew DeSilver. Pew Research Center, December 5, 2013. <www.pewresearch.org>

Emmanuel Saez, an economics professor at UC-Berkeley, has been doing just that for years. And according to his research, U.S. income inequality has been increasing steadily since the 1970s, and now has reached levels not seen since 1928. …

… But starting in the mid- to late 1970s, the uppermost tier’s income share began rising dramatically, while that of the bottom 90% started to fall. The top 1% took heavy hits from the dot-com crash and the Great Recession but recovered fairly quickly: Saez’s preliminary estimates for 2012 (which will be updated next month) have that group receiving nearly 22.5% of all pretax income, while the bottom 90%’s share is below 50% for the first time ever (49.6%, to be precise).

[223] Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “3. Number of Households, Average Income, and Shares of Income for All Households, by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[224] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 2: “In 2013, according to the Congressional Budget Office’s estimates, average household market income—a comprehensive income measure that consists of labor income, business income, capital income (including capital gains), and retirement income—was approximately $86,000.”

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[225] Webpage: “Warren: The Average Family in the Bottom 90 Percent Made More Money 30 Years Ago.” PolitiFact, January 13, 2015. <www.politifact.com>

To check out Warren’s claim, we looked at average income data from 1979 to 2012 for the top 10 percent and bottom 90 percent of earners. (The time frame Warren used in her speech was “a generation,” which is vague, but in context it’s clear she’s talking about since the 1980s.) The Saez-Piketty data comes from millions of tax returns filed over the past century. …

We rate Warren’s claim Mostly True.

[226] Article: “U.S. Income Inequality, on Rise for Decades, Is Now Highest Since 1928.” By Drew DeSilver. Pew Research Center, December 5, 2013. <www.pewresearch.org>

Using tax-return data from the IRS, Saez has built extensive income-distribution datasets going back 100 years. He defines “income” as pre-tax cash market income—wages and salaries; dividends, interest, rent and other returns on invested capital; business profits; and realized capital gains. He excludes Social Security payments, unemployment benefits and other government transfer payments, which are more substantial today than before the Great Depression.

[227] Article: “Review: ‘The Economics of Inequality,’ by Thomas Piketty.” By Paul Krugman. New York Times, August 2, 2015. <www.nytimes.com>

Back in 2001 two French economists, Thomas Piketty and Emmanuel Saez, circulated a seminal research paper (formally published two years later) titled “Income inequality in the United States, 1913–1998.” …

… It was a landmark piece of research that has had a major impact, not just on economics, but on political science too, for the fall and rise of the 1 percent turns out to be closely correlated with the fall and rise of political polarization. And last year, of course, Mr. Piketty made a huge splash with his magnum opus, “Capital in the Twenty-First Century,” which both exposed the startling facts about inequality to a wide audience and made a disturbing case that we are well on the way to re-establishing “patrimonial capitalism,” a society dominated by oligarchs who inherit their wealth.

[228] Article: “Response by Thomas Piketty and Emmanuel Saez to: ‘The Top 1% … of What?’ by Alan Reynolds.” By Thomas Piketty and Emmanuel Saez. University of California, Berkeley, December 20, 2006. <eml.berkeley.edu>

Page 1 (of PDF):

Our measure of income is cash market income defined as gross income reported on tax returns less government transfers such as Social Security or Unemployment Insurance. Personal income is a broader measure of income which also includes non-cash market income such as fringe benefits from employers, imputed rent for homeowners, under-reported income (due to tax evasion) but also government transfers such as Medicare, Social Security. Conceptually, it makes more sense to focus either on market income (before deducting taxes and including transfers) or on disposable income (market income net of taxes and including transfers). We chose to estimate inequality based on (cash) market income but it would certainly be interesting to estimate inequality based on disposable income as well to assess the effects of government taxes and transfers on inequality.

[229] Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “6. Sources of Income for All Households, by Before-Tax Income Group, 1979 to 2013”

NOTE: An Excel file containing the data and calculations is available upon request.

[230] Paper: “Income Inequality in the United States, 1913–1998.” By Thomas Piketty and Emmanuel Saez. Quarterly Journal of Economics, February 2003. <eml.berkeley.edu>

Page 4: “Our estimations rely on tax returns statistics compiled annually by the Internal Revenue Service since the beginning of the modern U. S. income tax in 1913.”

Pages 5–6:

We use a gross income definition including all income items reported on tax returns and before all deductions: salaries and wages, small business and farm income, partnership and fiduciary income, dividends, interest, rents, royalties, and other small items reported as other income. Realized capital gains are not an annual flow of income (in general, capital gains are realized by individuals in a lumpy way) and form a very volatile component of income with large aggregate variations from year to year depending on stock price variations. Therefore, we focus mainly on series that exclude capital gains. Income, according to our definition, is computed before individual income taxes and individual payroll taxes but after employers’ payroll taxes and corporate income taxes.

[231] Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “6. Sources of Income for All Households, by Before-Tax Income Group, 1979 to 2013”

NOTE: An Excel file containing the data and calculations is available upon request.

[232] Paper: “Income Inequality in the United States, 1913–1998.” By Thomas Piketty and Emmanuel Saez. The Quarterly Journal of Economics, February 2003. <eml.berkeley.edu>

Page 4: “Our estimations rely on tax returns statistics compiled annually by the Internal Revenue Service since the beginning of the modern U. S. income tax in 1913.”

Pages 5–6:

We use a gross income definition including all income items reported on tax returns and before all deductions: salaries and wages, small business and farm income, partnership and fiduciary income, dividends, interest, rents, royalties, and other small items reported as other income. Realized capital gains are not an annual flow of income (in general, capital gains are realized by individuals in a lumpy way) and form a very volatile component of income with large aggregate variations from year to year depending on stock price variations. Therefore, we focus mainly on series that exclude capital gains. Income, according to our definition, is computed before individual income taxes and individual payroll taxes but after employers’ payroll taxes and corporate income taxes.

[233] Calculated with the dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “3. Number of Households, Average Income, and Shares of Income for All Households, by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides relevant context about this data.

[234] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 6:

For this analysis, federal taxes include individual income taxes, payroll taxes, corporate income taxes, and excise taxes, which together accounted for 93 percent of all federal revenues in fiscal year 2013. Revenues from states’ deposits for unemployment insurance, estate and gift taxes, miscellaneous fees and fines, and net income earned by the Federal Reserve, which make up the remaining 7 percent, are not allocated to households in this analysis, mainly because it is uncertain how to attribute those revenues to particular households.

Page 11: “Because of the complexity of estimating state and local taxes for individual households, this report considers federal taxes only. Researchers differ about whether state and local taxes are, on net, regressive, proportional, or slightly progressive, but most agree that state and local taxes are less progressive than federal taxes.”

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[235] Paper: “Income Inequality in the United States, 1913–1998.” By Thomas Piketty and Emmanuel Saez. The Quarterly Journal of Economics, February 2003. <eml.berkeley.edu>

Page 2:

To cast light on this central issue, we build new homogeneous series on top shares of pretax income and wages in the United States covering the 1913 to 1998 period. These new series are based primarily on tax returns data published annually by the Internal Revenue Service (IRS) since the income tax was instituted in 1913, as well as on the large micro-files of tax returns released by the IRS since 1960.

Page 4:

Our estimations rely on tax returns statistics compiled annually by the Internal Revenue Service since the beginning of the modern U. S. income tax in 1913. Before 1944, because of large exemptions levels, only a small fraction of individuals had to file tax returns and therefore, by necessity, we must restrict our analysis to the top decile of the income distribution.4 Because our data are based on tax returns, they do not provide information on the distribution of individual incomes within a tax unit. As a result, all our series are for tax units and not individuals. A tax unit is defined as a married couple living together (with dependents) or a single adult (with dependents), as in the current tax law. As a result, all our series are for tax units and not individuals.

4 From 1913 to 1916, because of higher exemption levels, we can provide estimates only within the top percentile.

[236] Paper: “A ‘Second Opinion’ On the Economic Health of the American Middle Class.” By Richard V. Burkhauser, Jeff Larrimore and Kosali I. Simon. National Tax Journal, March 2012. <classes.igpa.uiuc.edu>

Page 9:

Indeed, it is often the case that an individual’s tax unit and household unit are exactly the same. A tax unit typically consists of an adult, his or her spouse, and any dependent children. Such a tax unit would include all of the members of a “traditional family arrangement” household. However, there are many situations in which this is not the case. For example, cohabiters, roommates who share expenses, children who move back in with their parents, or older parents who live with their adult children are households that contain more than one tax unit.

Page 10:

When we analyze median income in the CPS data using tax units, we find that the pre-tax, pre-transfer income (the market income) of the median tax unit decreased over the 2000–2007 business cycle. This is the case whether we focus solely on those tax units who file a return or on all tax units regardless of whether they file a return. Potentially more disturbing, the median pre-tax, pre-transfer income of all tax units (filers and non-filers) only increased by 3.2 percent in real terms over the entire period between 1979–2007. These results are consistent with the view that the typical American has not gained much from economic growth over the last 30 years.

But when we broaden the sharing unit to the household, account for economies of scale in household consumption, and recognize that the payment of taxes or the receipt of tax credits as well as government transfer income and in-kind benefits all impact the economic resources available to individuals, we find the story changes. Specifically, when using our broadest measure of available resources—post-tax, post-transfer, size-adjusted household income including the ex-ante value of in-kind health insurance benefits—median income growth of individual Americans improves to 36.7 percent over the period from 1979–2007, and by 4.8 percent between 2000–2007. Similarly, these choices impact the observed distribution of income and the extent to which incomes at the top of the distribution are growing faster than those of the middle and lower classes.

[237] Report: “A Record 21.6 Million In 2012—A Rising Share of Young Adults Live in Their Parents’ Home.” By Richard Fry. Pew Research Center, August 1, 2013. <www.pewsocialtrends.org>

Page 1:

In 2012, 36% of the nation’s young adults ages 18 to 31—the so-called Millennial generation—were living in their parents’ home, according to a new Pew Research Center analysis of U.S. Census Bureau data. This is the highest share in at least four decades and represents a slow but steady increase over the 32% of their same-aged counterparts who were living at home prior to the Great Recession in 2007 and the 34% doing so when it officially ended in 2009. …

Notes: “Living at home” refers to an adult who is the child or stepchild of the head of the household, regardless of the adult’s marital status.

Source: Pew Research Center tabulations of March 2012 Current Population Survey (CPS) Integrated Public Use Micro Sample

[238] Calculated with the dataset: “HH-1. Households by Type: 1940 to Present.” U.S. Census Bureau, November 2016. <www.census.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[239] Paper: “Measures of Income Inequality Are Biased or Misinterpreted.” By Ivan Kitov. Social Science Research Network, December 10, 2014. <papers.ssrn.com>

Page 1: “The changing composition of households in the U.S. is the effect explaining the reported increase in Gini coefficient for households since 1967. When corrected for actual decrease in the average household size the relevant Gini coefficient returns to that of personal incomes.”

Page 6:

In Figure 7a, we present the Gini coefficient for households. We intentionally normalized the ratio to its maximum value (0.477 in 2011) in order to show that this inequality measure has risen by 20% since 1967. This dramatic increase is interpreted as a big problem for the US but contradicts the observation of constant Gini coefficient for individuals. Unlike personal incomes, the household data are collected for entities which can evolve in size. … Actually, the fall in the average size is quite spectacular: from 3.2 in 1967 to 2.49 in 2011. The simplest effect leading to the observed size decrease is household split—instead of one big household two smaller households appear. Obviously, the Gini coefficient depends on the distribution of household sizes. For fixed total income, the increasing number of households (split), which share the same amount of money, should result in a higher Gini coefficient. When all households are split to the smallest pieces (one person households) we have the personal income distribution with a larger Gini.

[240] Paper: “Measures of Income Inequality Are Biased or Misinterpreted.” By Ivan Kitov. Social Science Research Network, December 10, 2014. <papers.ssrn.com>

Page 1: “The changing composition of households in the U.S. is the effect explaining the reported increase in Gini coefficient for households since 1967. When corrected for actual decrease in the average household size the relevant Gini coefficient returns to that of personal incomes.”

Page 6:

In Figure 7a, we present the Gini coefficient for households. We intentionally normalized the ratio to its maximum value (0.477 in 2011) in order to show that this inequality measure has risen by 20% since 1967. This dramatic increase is interpreted as a big problem for the US but contradicts the observation of constant Gini coefficient for individuals. Unlike personal incomes, the household data are collected for entities which can evolve in size. … Actually, the fall in the average size is quite spectacular: from 3.2 in 1967 to 2.49 in 2011. The simplest effect leading to the observed size decrease is household split—instead of one big household two smaller households appear. Obviously, the Gini coefficient depends on the distribution of household sizes. For fixed total income, the increasing number of households (split), which share the same amount of money, should result in a higher Gini coefficient. When all households are split to the smallest pieces (one person households) we have the personal income distribution with a larger Gini.

[241] Chart constructed with data from:

a) Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab 3: “Number of Households, Average Income, and Shares of Income for All Households, by Before-Tax Income Group, 1979 to 2013”

b) Dataset: “Fiscal Income Share, Top 10%, Middle 40%, and Bottom 50%, USA, 1979–2013.” World Wealth & Income Database.†‡ Accessed May 11, 2017 at <wid.world>

NOTES:

  • † Webpage: “World Wealth & Income Database.” Accessed December 2, 2017 at <wid.world>
    “During the past fifteen years, the renewed interest for the long-run evolution of income and wealth inequality gave rise to a flourishing literature. In particular, a succession of studies has constructed top income share series for a large number of countries (see Thomas Piketty 2001, 2003, T. Piketty and Emmanuel Saez 2003, and the two multi-country volumes on top incomes edited by Anthony B. Atkinson and T. Piketty 2007, 2010; see also A. B. Atkinson et al. 2011 and Facundo Alvaredo et al. 2013 for surveys of this literature). These projects generated a large volume of data, intended as a research resource for further analysis, as well as a source to inform the public debate on income inequality.”
  • ‡ Webpage: “Team.” World Wealth & Income Database. Accessed December 2, 2017 at <wid.world>
    “The World Wealth and Income Database (WID.world) relies on the combined effort of an international network of over a hundred researchers covering more than seventy countries from all continents. WID.world is coordinated by an executive committee composed of five co-directors … Facundo Alvaredo … Lucas Chancel … Thomas Piketty … Emmanuel Saez … Gabriel Zucman”
  • An Excel file containing the data and calculations is available upon request.
  • The next footnote provides context about the CBO data.

[242] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 2: “In 2013, according to the Congressional Budget Office’s estimates, average household market income—a comprehensive income measure that consists of labor income, business income, capital income (including capital gains), and retirement income—was approximately $86,000.”

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[243] Article: “Response by Thomas Piketty and Emmanuel Saez to: ‘The Top 1% … of What?’ by Alan Reynolds.” By Thomas Piketty and Emmanuel Saez. University of California, Berkeley, December 20, 2006. <eml.berkeley.edu>

Page 1 (of PDF):

Alan Reynolds points out that transfers have increased since 1980 but taxes on high incomes have decreased substantially. Actually, we have estimated that the average Federal tax burden on top 1% families has decreased from 44.4% in 1980 to 30.4% in 2004. The decrease in taxes at the top outweighs the increase in transfers at the bottom. Therefore, the top 1% disposable income share has most likely more than doubled since 1980.

[244] Dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “1. Average Federal Tax Rates for All Households, by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • See Just Facts’ research on tax distribution for other examples of how prominent individuals have reported misleading tax rates by excluding selected taxes and sources of income from their analyses.
  • The next footnote provides relevant context about this data.

[245] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 6:

For this analysis, federal taxes include individual income taxes, payroll taxes, corporate income taxes, and excise taxes, which together accounted for 93 percent of all federal revenues in fiscal year 2013. Revenues from states’ deposits for unemployment insurance, estate and gift taxes, miscellaneous fees and fines, and net income earned by the Federal Reserve, which make up the remaining 7 percent, are not allocated to households in this analysis, mainly because it is uncertain how to attribute those revenues to particular households.

Page 11: “Because of the complexity of estimating state and local taxes for individual households, this report considers federal taxes only. Researchers differ about whether state and local taxes are, on net, regressive, proportional, or slightly progressive, but most agree that state and local taxes are less progressive than federal taxes.”

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[246] Article: “Response by Thomas Piketty and Emmanuel Saez to: ‘The Top 1% … of What?’ by Alan Reynolds.” By Thomas Piketty and Emmanuel Saez. University of California, Berkeley, December 20, 2006. <eml.berkeley.edu>

Page 1 (of PDF):

Alan Reynolds points out that transfers have increased since 1980 but taxes on high incomes have decreased substantially. Actually, we have estimated that the average Federal tax burden on top 1% families has decreased from 44.4% in 1980 to 30.4% in 2004. The decrease in taxes at the top outweighs the increase in transfers at the bottom. Therefore, the top 1% disposable income share has most likely more than doubled since 1980.

[247] Calculated with the dataset: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Tab: “1. Average Federal Tax Rates for All Households, by Before-Tax Income Group, 1979 to 2013”

Tab: “3. Number of Households, Average Income, and Shares of Income for All Households, by Before-Tax Income Group, 1979 to 2013”

Tab: “6. Sources of Income for All Households, by Before-Tax Income Group, 1979 to 2013”

NOTES:

  • An Excel file containing the data and calculations is available upon request.
  • See Just Facts’ research on tax distribution for other examples of how prominent individuals have reported misleading tax rates by excluding selected taxes and sources of income from their analyses.
  • The next footnote provides relevant context about this data.

[248] Report: “The Distribution of Household Income and Federal Taxes, 2013.” Congressional Budget Office, June 2016. <www.cbo.gov>

Page 6:

For this analysis, federal taxes include individual income taxes, payroll taxes, corporate income taxes, and excise taxes, which together accounted for 93 percent of all federal revenues in fiscal year 2013. Revenues from states’ deposits for unemployment insurance, estate and gift taxes, miscellaneous fees and fines, and net income earned by the Federal Reserve, which make up the remaining 7 percent, are not allocated to households in this analysis, mainly because it is uncertain how to attribute those revenues to particular households.

Page 11: “Because of the complexity of estimating state and local taxes for individual households, this report considers federal taxes only. Researchers differ about whether state and local taxes are, on net, regressive, proportional, or slightly progressive, but most agree that state and local taxes are less progressive than federal taxes.”

Page 24:

Data Sources on Household Income

Information on household income for this analysis came from two primary sources: the Internal Revenue Service’s Statistics of Income (SOI) and the Census Bureau’s Current Population Survey (CPS). The core data came from the SOI, a nationally representative sample of individual income tax returns. The number of returns sampled grew over the time period studied, ranging from roughly 90,000 in some of the early years to more than 300,000 in the later years. CBO used the full Individual Income Tax file, which is more detailed than the public-use version of the file. The agency supplemented those data with data from the CPS’s Annual Social and Economic Supplement; those data identify demographic characteristics and income for a large sample of households.

Pages 26–27:

Measures of Income

This analysis uses three measures of household income: market income, market income plus government transfers (before-tax income), and market income plus government transfers minus federal taxes (after-tax income).

Market income consists of these components:

Labor Income. Cash wages and salaries, including amounts allocated by employees to 401(k) plans; employer-paid health insurance premiums; the employer’s share of Social Security, Medicare, and federal unemployment insurance payroll taxes; and the share of corporate income taxes borne by workers.†

Business Income. Net income from businesses and farms operated solely by their owners, partnership income, and income from S corporations.

Capital Gains. Profits realized from the sale of assets, excluding increases in the value of assets that have not been realized through sales.

Capital Income Excluding Capital Gains. Taxable and tax-exempt interest, dividends paid by corporations (but not dividends paid by S corporations, which are considered part of business income), positive rental income, and the share of corporate income taxes borne by owners of capital.†

Other Income. Income received in retirement for past services or from other sources.

Government transfers consist of the cost of two types of benefits:

Cash. Payments from Social Security, unemployment insurance, Supplemental Security Income, Temporary Assistance for Needy Families (and its predecessor, Aid to Families With Dependent Children), veterans’ programs, workers’ compensation, and state and local government assistance programs.

In-Kind Benefits. The cost of Supplemental Nutrition Assistance Program vouchers (popularly known as food stamps); school lunches and breakfasts; housing assistance; energy assistance; and benefits provided by Medicare, Medicaid, and the Children’s Health Insurance Program.

† NOTE: See Just Fact’s research on the distribution of the federal tax burden for details about how the Congressional Budget Office determines the share of corporate income taxes borne by workers and owners of capital.

[249] Paper: “Is More Always Better? A Survey on Positional Concerns.” By Sara J. Solnick and David Hemingway. Journal of Economic Behavior & Organization, July 1997. <www.sciencedirect.com>

Page 377:

In February 1995, 257* faculty, students and staff at the Harvard School of Public Health responded to a survey. The survey consisted of twelve questions in the same format (see Appendix A). Each question presented two states of the world. In each state of the world, respondents were told how much they had of a certain good, bad, or personal attribute, and how much the typical other person in society had. Amounts were structured so that in one case, the “positional” case, the respondent had more than others in society. In the other case, the “absolute” case, amounts for both respondents and others were greater than in the positional case, but respondents had less than others in society. Two examples are given below:

A: Your current yearly income is $50,000; others earn $25,000.

B: Your current yearly income is $100,000; others earn $200,000. (Prices are what they are currently and prices (therefore the purchasing power of money) are the same in states A and B.) …

… Here State A is the positional and State B, the absolute case. Respondents were asked to indicate which of the two worlds they would prefer to live in. …

Page 378:

When the positional state of the world is first, the second state has more for everyone. This configuration will be called the “gain” survey, because absolute amounts are higher for goods (lower for bads) in the second state than in the first state. When the positional state is listed second, everyone’s endowment is greater in the first state. This arrangement will be called the “loss” survey, because amounts are lower for goods (higher for bads) in the second state. …

… Approximately 50 percent of the respondents preferred a world in which they had half the real purchasing power, as long as their relative income position was high (Table 1). …

Table 1

Positional Concern by Type of Good

Percentage Giving “Positional” Answer

“Gain” (N=146)

“Loss” (N=101)

Total (N=247) †

Child’s attractiveness

80

56

70

Praise from supervisor

77

58

69

Own attractiveness

75

55

67

Child’s intelligence

71

52

63

Own intelligence

68

49

60

Child’s education

56

40

49

Income

56

38

49

Own education

50

31

42

Berated by supervisor

33

40

36

Papers to write

31

24

28

Vacation (Q 3)

18

14

16

Vacation (Q 11)

18

10

15

NOTES:

  • * The figure of “257” respondents in the abstract is inconsistent with the data in the table above, which shows 247 respondents (146 + 101).
  • † Calculated by Just Facts.
  • An Excel file containing the data and calculations is available upon request.

[250] Book: Introductory Econometrics: Using Monte Carlo Simulation with Microsoft Excel. By Humberto Barreto and Frank M. Howland. Cambridge University Press, 2006.

Page 43:

Association Is Not Causation

A second problem with the correlation coefficient involves its interpretation. A high correlation coefficient means that two variables are highly associated, but association is not the same as causation.

This issue is a persistent problem in empirical analysis in the social sciences. Often the investigator will plot two variables and use the tight relationship obtained to draw absolutely ridiculous or completely erroneous conclusions. Because we so often confuse association and causation, it is extremely easy to be convinced that a tight relationship between two variables means that one is causing the other. This is simply not true.

[251] Article: “Statistical Malpractice.” By Bruce G. Charlton. Journal of the Royal College of Physicians of London, March 1996. Pages 112–114. <www.researchgate.net>

Page 112: “Science is concerned with causes but statistics is concerned with correlations.”

Page 113: “The root of most instances of statistical malpractice is the breaking of mathematical neutrality and the introduction of causal assumptions into analysis without justifying them on scientific grounds.”

[252] Book: Business and Competitive Analysis: Effective Application of New and Classic Methods (2nd edition). By Craig S. Fleisher and Babette E. Bensoussan. Pearson Education, 2015.

Pages 338–339: “One of the biggest potential problems with statistical analysis is the quality of the interpretation of the results. Many people see cause-and-effect relationships ‘evidenced’ by statistics, which are in actuality simply describing data associations or correlation having little or nothing to do with casual factors.”

[253] Dataset: “People 25 Years Old and Over, by Total Money Earnings in 2017.”  U.S. Census Bureau. Accessed November 16, 2018 at <www2.census.gov>

“Both Sexes, 25 to 64 Years, Total Work Experience, All Races”

NOTE: An Excel file containing the data and calculations is available upon request.

[254] Webpage: “Academic Degree and Certificate Definitions.” Arkansas Department of Higher Education, Research and Planning Division. Accessed July 17, 2015 at <www.adhe.edu>

Associate degree (two years or more): a degree granted upon completion of a program that requires at least two, but fewer than four, academic years of postsecondary education. It includes a level of general education necessary for growth as a lifelong learner and is comprised of 60–72 semester credit hours. There are four types of associate degrees: …

Baccalaureate (bachelor’s) degree: a degree granted upon completion of a program that requires four to five years of full-time college work and carries the title of bachelor. …

Master’s degree: a degree which requires at least one, but no more than two, full-time equivalent years of study beyond the bachelor’s degree.

Doctoral degree: a degree awarded upon completion of an educational program at the graduate level which terminates in a doctor’s degree. …

First professional degree: a degree awarded upon completion of a program which meets all of these criteria: a) completion of academic requirements to begin practice in the profession; b) at least two years of college work before entering the program; and c) at least six academic years of college work to complete the degree program, including the prior required college work. First professional degrees are awarded in these fields:

• Chiropractic (DC)

• Dentistry (DDS or DMD)

• Law (LLB or JD)

• Medicine (MD)

• Optometry (OD)

• Osteopathic Medicine (DO)

• Pharmacy (Pharm.D.)

• Podiatry (Pod D or DP)

• Theology (M Div or MHL)

• Veterinary Medicine (DVM)

[255] Dataset: “People 25 Years Old and Over, by Total Money Earnings in 2017.”  U.S. Census Bureau. Accessed November 16, 2018 at <www2.census.gov>

“Both Sexes, 25 to 64 Years, Total Work Experience, All Races”

NOTE: An Excel file containing the data and calculations is available upon request.

[256] Webpage: “Occupational Outlook Handbook.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed April 25, 2017 at <www.bls.gov>

Highest Paying Occupations

Occupation

2016 Median Pay

Surgeons

This wage is equal to or greater than $208,000 per year

Oral and maxillofacial surgeons

This wage is equal to or greater than $208,000 per year

Obstetricians and gynecologists

This wage is equal to or greater than $208,000 per year

Orthodontists

This wage is equal to or greater than $208,000 per year

Anesthesiologists

This wage is equal to or greater than $208,000 per year

Physicians and surgeons, all other

$206,920 per year

Internists, general

$196,380 per year

Psychiatrists

$194,740 per year

Family and general practitioners

$190,490 per year

Chief executives

$181,210 per year

Dentists, all other specialists

$173,000 per year

Pediatricians, general

$168,990 per year

Nurse anesthetists

$160,270 per year

Dentists, general

$153,900 per year

Computer and information systems managers

$135,800 per year

Architectural and engineering managers

$134,730 per year

Marketing managers

$131,180 per year

Petroleum engineers

$128,230 per year

Airline pilots, copilots, and flight engineers

$127,820 per year

Prosthodontists

$126,050 per year

[257] Webpage: “About the EPPI-Center.” EPPI-Centre, University of London. Accessed May 31, 2017 at <eppi.ioe.ac.uk>

About the EPPI-Centre

The EPPI-Centre is a specialist centre for: (i) developing methods for systematic reviewing and synthesis of research evidence; and (ii) developing methods for the study of the use research.

We have very close links with the main international collaborations in synthesis methods and we are partners or undertake other work with many of the UK government what works centres. We are interested in complexity and mixed methods reviews to understand research relevant to decision making as well as methods for how that research is used in practice. We see research as both a crucially important form of academic enquiry and as an important resource for use in society.

As well as being directly involved in research synthesis and research use, we provide two MSc programmes and many short courses in research synthesis and social policy and research. We also produce many publications on research synthesis and research use.

Our work in research synthesis and research use is across many areas of social policy including education, health, social care, developing economies, sport, environment, and crime.

The EPPI-Centre is based in the Social Science Research Unit in the Department of Social Science, UCL Institute of Education, University College London. The work of the centre started in 1993, the name ‘EPI-Centre’ was used from 1995 and we then changed to the current name of ‘EPPI-Centre’ from 2001.

[258] Report: “Evidence on the Economic Growth Impacts of Corruption in Low-Income Countries and Beyond: A Systematic Review.” By Mehmet Ugur and Nandini Dasgupta. EPPI-Centre, University of London, August 2011. <eppi.ioe.ac.uk>

Page 1: “After critical evaluation, the total number of studies included for narrative synthesis and meta-analysis was 115.”

Page 7:

The direct effect of corruption on per capita GDP growth in LICs [Low Income Countries] is statistically significant and negative (-0.07 percentage point), but low. The indirect effects through the public finance and human capital channels are higher (−0.23 and −0.29 percentage points, respectively). Hence, the total effect that satisfies the precision-effect test is −0.59 percentage point. This should be interpreted as follows: a one-unit increase in the perceived corruption index of a low-income country can be expected to lead to a fall of 0.59 percentage point in the growth rate of its per capita GDP. The corresponding effect in “mixed” countries (including LICs and more developed countries) is −0.86 percentage point.

Page 8: “Corruption has a negative and statistically significant effect on per capita GDP growth in LICs and non-LICs, but its effect in non-LICs is higher. Therefore, corruption should be considered as an international problem with varying degrees of adverse economic consequences rather than as a problem confined to low income countries.”

Page 81:

Focusing on per capita GDP growth, we can put the synthesised evidence into perspective as follows: suppose a hypothetical LIC had a per capita GDP of $500 in 1995 and has achieved an average of 3 percent growth from 1995 to 2010 (16 years). If the corruption level had remained the same in this hypothetical country, its per capita GDP would have been $802 in 2010. However, if this country had reduced the corruption level by one unit in 1995 and if it had kept the level of corruption constant in the following years, its per capita GDP would have been $879 in 2010. In other words, per capita GDP in this hypothetical country would have been 10 percent higher than the baseline figure if corruption had been reduced by one unit in 1995 and kept constant thereafter.

Page 88: “Subject to limitations associated with the meta-analysis of observational study estimates, the evidence synthesised in this review indicates that corruption has negative and statistically significant effects on growth—directly and indirectly, and in both LICs and non-LICs.”

[259] Textbook: Macroeconomics (10th edition). By William Boyes and Michael Melvin. Cengage Learning, 2015.

Page 84:

Modern economies produce an amazing variety of goods and services. To measure an economy’s total production, economists combine the quantities of oranges, golf balls, automobiles, and all the other goods and services produced into a single measure of output. Of course, simply adding up the number of things produced—the number of oranges, golf balls, and automobiles—does not reveal the value of what is being produced. If a nation produces 1 million more oranges and 1 million fewer automobiles this year than it did last year, the total number of things produced remains the same. But because automobiles are much more valuable than oranges, the value of the nation’s output has dropped substantially. Prices reflect the value of goods and services in the market, so economists use the money value of things to create a measure of total output, a measure that is more meaningful than the sum of the units produced.

The most common measure of a nation’s output is gross domestic product. Gross domestic product (GDP) is the market value of all final goods and services produced in a year within a country’s borders.

[260] Report: “International Comparisons of GDP Per Capita and Per Hour, 1960–2011.” U.S. Bureau of Labor Statistics, November 7, 2012. <www.bls.gov>

Page 2:

Gross Domestic Product (GDP) is defined as the value of all market and some nonmarket goods and services produced within a country’s geographic borders. As such, it is the most comprehensive measure of a country’s economic output that is estimated by statistical agencies. GDP per capita may therefore be viewed as a rough indicator of a nation’s economic well-being, while GDP per hour worked can provide a general picture of a country’s productivity.

[261] Textbook: Microeconomics for Today (9th edition). By Irvin B. Tucker. South-Western Cengage Learning, 2016.

Page 473: “GDP per capita provides a general index of a country’s standard of living. Countries with low GDP per capita and slow growth in GDP per capita are less able to satisfy basic needs for food, shelter, clothing, education, and health.”

[262] Book review: “The Elusive Quest for Growth: Economists’ Adventures and Misadventures in the Tropics.” By William Easterly. MIT Press, 2001.” By Terry J. Fitzgerald (Senior Economist and Assistant Vice President of the Federal Reserve Bank of Minneapolis). The Region, September 2003. <www.minneapolisfed.org>

Economists are sometimes criticized for focusing their attention on gross domestic product per capita, or income per person, as a measure of the material success of an economy. Easterly explains why they do: “We experts don’t care about rising gross domestic product for its own sake. We care because it betters the lot of the poor and reduces the proportion of people who are poor. We care because richer people can eat more and buy more medicines for their babies.”

Still, an important empirical question is whether national economic growth raises the incomes of those in poverty, not just those who are already well off. Here Easterly provides the reader with an overview of the evidence on poverty and growth and reports that the answer is a clear yes. (Throughout the book the author offers readers numerous direct references should they wish to peruse the evidence on their own.) And in a statement that may rankle some, Easterly provocatively offers that “growth has been much more of a lifesaver to the poor than redistribution.” Indeed, recent research by Xavier Sala-i-Martin of Columbia University—released after The Elusive Quest’s publication—finds that poverty has declined dramatically worldwide over the past three decades as incomes have risen. Yet, not all would concede Easterly’s point.

[263] Working paper: “Growth is Good for the Poor.” By David Dollar and Aart Kraay. World Bank, April 2001. <library1.nida.ac.th>

Page 5:

Income of the poor has a very tight link with overall incomes. The top panel of Figure 1 shows the logarithm of average income in the poorest fifth of the population plotted against the logarithm of average income for the whole economy (per capita GDP). The graph includes 418 observations covering 137 countries, and multiple observations for a single country are separated by at least five years over time. The slope of this relationship is very close to one, and all of the observations are closely clustered around this regression line. This indicates that as overall income increases, on average incomes of the poor increase equiproportionately.

[264] Chart constructed with data from:

a) Dataset: “Corruption Perceptions Index 2016.” Transparency International, January 25, 2017. <files.transparency.org>

Tab: “CPI2015_2016 … CPI2015 score”

b) Dataset: “GDP Per Capita, PPP (Current International $).” World Bank, March 23, 2017. <data.worldbank.org>

Tab: “Data … 2015”

NOTES:

  • The chart is cropped to improve data visibility, and hence, it does not show several outliers. These outliers don’t materially impact the overall trend.
  • See the forthcoming footnotes for information about the Transparency International index.
  • An Excel file containing the data is available upon request.

[265] Webpage: “Corruption Perceptions Index 2016: Frequently Asked Questions.” Transparency International, January 23, 2017. <files.transparency.org>

Page 1:

What is the Corruption Perceptions Index (CPI)?

The CPI scores and ranks countries/territories based on how corrupt a country’s public sector is perceived to be. It is a composite index, a combination of surveys and assessments of corruption, collected by a variety of reputable institutions. The CPI is the most widely used indicator of corruption worldwide. …

What are the data sources for the CPI?

The 2016 CPI draws on data sources from independent institutions specialising in governance and business climate analysis. The sources of information used for the 2016 CPI are based on data gathered in the past 24 months. The CPI includes only sources that provide a score for a set of countries/territories and that measure perceptions of corruption in the public sector. Transparency International reviews the methodology of each data source in detail to ensure that the sources used meet Transparency International’s quality standards.

[266] “Corruption Perceptions Index 2016: Short Methodology Note.” Transparency International, January 19, 2017. <files.transparency.org>

“The CPI 2016 is calculated using 13 different data sources from 12 different

institutions that capture perceptions of corruption within the past two years.

These sources are described in detail in the accompanying source description

document.”

[267] “Corruption Perceptions Index 2016: Technical Methodology Note.” Transparency International, January 19, 2017. <files.transparency.org>

Pages 1–2:

Selection of data sources

The CPI draws upon a number of available sources which capture perceptions of

corruption. Each source is evaluated against the criteria listed below. Contact has

been made with each institution providing data in order to verify the methodology

used to generate scores and for permission to publish the rescaled scores from each

source, alongside the composite index score.

A) Reliable data collection and methodology from a credible institution ….

B) Data addresses corruption in the public sector….

C) Quantitative granularity….

D) Cross country comparability….

E) Multi year data-set….

[268] Book: Where is the Wealth of Nations?: Measuring Capital for the 21st Century. By Kirk Hamilton, Giovanni Ruta, and others. World Bank, 2006. <documents.worldbank.org>

Page 19:

What constitutes wealth? Traditionally attention has been focused on produced capital such as buildings, machinery, equipment, and infrastructure. The wealth estimates introduced below extend these measures by accounting for exhaustible resources, renewable resources, and agricultural land. The estimates also include intangible capital, which encompasses raw labor, human capital (the stock of human skills and know-how), social capital, and the quality of institutions.

Page 23:

Natural capital is the sum of nonrenewable resources (including oil, natural gas, coal, and mineral resources), cropland, pastureland, forested areas (including areas used for timber extraction and non-timber forest products), and protected areas. The values for non-timber forest resources and protected areas are estimated only crudely. In the case of non-timber forest products, world average values of benefits per hectare, distinguishing developed and developing countries, are applied to a share of the country’s forested area (values are derived from Lampietti and Dixon 1995). Protected areas are valued using country-specific per-hectare values for cropland or pastureland (whichever is lower). This severely undervalues the Serengeti Plain, for example, but possibly overvalues some of the Arctic parks.

[269] Book: Where is the Wealth of Nations?: Measuring Capital for the 21st Century. By Kirk Hamilton, Giovanni Ruta, and others. World Bank, 2006. <documents.worldbank.org>

Page 22: “Produced capital is the sum of machinery, equipment, and structures (including infrastructure). Urban land is not considered to be a natural resource, and so is lumped in with produced capital in the wealth estimates. The value of urban land is calculated as a percentage of the value of machinery, equipment, and structures.”

[270] Book: Where is the Wealth of Nations?: Measuring Capital for the 21st Century. By Kirk Hamilton, Giovanni Ruta, and others. World Bank, 2006. <documents.worldbank.org>

Page 88:

[I]n most countries intangible capital is the largest share of total wealth. What does intangible capital measure in the wealth estimates? By construction, it captures all those assets that are not accounted for elsewhere. It includes human capital, the skills and know-how embodied in the labor force. It encompasses social capital, that is, the degree of trust among people in a society and their ability to work together for common purposes. It also includes those governance elements that boost the productivity of the economy. For example, if an economy has a very efficient judicial system, clear property rights, and an effective government, the result will be a higher total wealth and thus an increase in the intangible capital residual.

[271] Book: Where is the Wealth of Nations?: Measuring Capital for the 21st Century. By Kirk Hamilton, Giovanni Ruta, and others. World Bank, 2006. <documents.worldbank.org>

Page VII:

This volume asks a key question: Where is the Wealth of Nations? Answering this question yields important insights into the prospects for sustainable development in countries around the world. The estimates of total wealth—including produced, natural, and human and institutional capital—suggest that human capital and the value of institutions (as measured by rule of law) constitute the largest share of wealth in virtually all countries.

Pages 5–6:

The total wealth estimates reported here are built upon a combination of top-down and bottom-up approaches. These are presented briefly in the next chapter and detailed in appendix 1. Total wealth, in line with economic theory, is estimated as the present value of future consumption. Produced capital stocks are derived from historical investment data using a perpetual inventory model (PIM).4 Natural resource stock values are based upon country-level data on physical stocks, and estimates of natural resource rents are based on world prices and local costs. Intangible capital then is measured as the difference between total wealth and the other produced and natural stocks.

4 Pritchett (2000) argues that cumulating investments in this way is likely to overstate the value of capital stocks in developing countries, because the method does not account for the profitability of these investments.

Page 28:

The most striking aspect of the wealth estimates is the high values for intangible capital. Nearly 85 percent of the countries in our sample have an intangible capital share of total wealth greater than 50 percent. This outcome validates the classical economists’ intuition that human capital and other intangibles play a major role in economic development.

[272] Book: Where is the Wealth of Nations?: Measuring Capital for the 21st Century. By Kirk Hamilton, Giovanni Ruta, and others. World Bank, 2006. <documents.worldbank.org>

Page XIV:

The wealth estimates suggest that the preponderant form of wealth worldwide is intangible capital—human capital and the quality of formal and informal institutions. Moreover, the share of produced assets in total wealth is virtually constant across income groups, with a moderate increase in produced capital intensiveness in middle-income countries. The share of natural capital in total wealth tends to fall with income, while the share of intangible capital rises. The latter point makes perfect sense—rich countries are largely rich because of the skills of their populations and the quality of the institutions supporting economic activity.

Page 88: “For example, if an economy has a very efficient judicial system, clear property rights, and an effective government, the result will be a higher total wealth and thus an increase in the intangible capital residual.”

[273] Calculated with data from:

a) Dataset: “The Changing Wealth of Nations, Total Wealth 2005.” World Bank. Accessed September 21, 2017 at <databank.worldbank.org>

b) Dataset: “Price Level Ratio of PPP Conversion Factor (GDP) to Market Exchange Rate, 1990–2016.” World Bank, International Comparison Program Database. Accessed September 21, 2017 at <api.worldbank.org>

[274] Book: Where is the Wealth of Nations?: Measuring Capital for the 21st Century. By Kirk Hamilton, Giovanni Ruta, and others. World Bank, 2006. <documents.worldbank.org>

Page 21: “Intangible capital appears with a negative sign in some instances, which is an empirical possibility given that it is calculated as a residual—the difference between total wealth and the sum of natural and produced resources.”

[275] Calculated with the dataset: “HH-1. Households by Type: 1940 to Present.” U.S. Census Bureau, November 2016. <www.census.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[276] Dataset: “2015 Median Household Income by Marital Status.” U.S. Census Bureau. Accessed April 27, 2017 at <www.census.gov>

NOTE: The next three footnotes contain methodological details about this data.

[277] Webpage: “Current Population Survey (CPS) Respondents.” U.S. Census Bureau. Last updated September 23, 2011. <www.bls.gov>

The Current Population Survey (CPS) is a monthly survey of households conducted by the Census Bureau for the Bureau of Labor Statistics. In addition to the national unemployment rate, it provides a comprehensive body of data on the labor force, employment, unemployment, the unemployment rate, persons not in the labor force, hours of work, earnings, and other demographic and labor force characteristics. …

You will be interviewed at your home or over the telephone by a Census Bureau employee. The survey is not conducted by mail, e-mail, or online. …

… Any household member 15 years of age or older can respond for the household. However, we would like to talk to someone who is knowledgeable about people in the household.

[278] Document: “Basic CPS Questionnaire, Labor Force Items.” U.S. Census Bureau, July 8, 2011. <www2.census.gov>

Pages 44–45:

Which category represents (your/name of reference person/the total combined income) (total combined income during the past 12 months?/ of all members of your FAMILY during the past 12 months?/ of all members of (name of reference person) ‘s FAMILY during the past 12 months?)

This includes money from jobs, net income from business, farm or rent, pensions, dividends, interest, social security payments and any other money income received (. / by members of (your/ name of reference person) FAMILY who are 15 years of age or older.)

[279] Report: “Income and Poverty in the United States: 2015 (Current Population Reports).” By Bernadette D. Proctor, Jessica L. Semega, and Melissa A. Kollar. U.S. Census Bureau, September 2016. <www.census.gov>

Page 3: “The income and poverty estimates shown in this report are based solely on money income before taxes and do not include the value of noncash benefits, such as those provided by the Supplemental Nutrition Assistance Program (SNAP), Medicare, Medicaid, public housing, or employer-provided fringe benefits.”

Page 21:

Data on income collected in the ASEC [Current Population Survey Annual

Social and Economic Supplements] by the Census Bureau cover money income received (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, Medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive noncash benefits, such as Supplemental Nutrition Assistance/food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents, which often take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc. Data users should consider these elements when comparing income levels. Moreover, readers should be aware that for many different reasons there is a tendency in household surveys for respondents to underreport their income. Based on an analysis of independently derived income estimates, the Census Bureau determined that respondents report income earned from wages or salaries more accurately than other sources of income, and that the reported wage and salary income is nearly equal to independent estimates of aggregate income.

[280] Report: “Breadwinner Moms.” By Wendy Wang, Kim Parker, and Paul Taylor. Pew Research Center, May 29, 2013. <www.pewsocialtrends.org>

Page 19:

Family Income of Two Types of Single Mothers

Median family income in 2011

All households with children [=] $57,100

Divorced, Separated, Widowed [=] $29,000

Never married [=] $17,400

Note: Based on families with own child(ren) under age 18 in the household.

Source: Pew Research Center analysis of 2011 American Community Survey (ACS) Integrated Public Use Microdata Sample (IPUMS) files

[281] Report: “Income and Poverty in the United States: 2015 (Current Population Reports).” By Bernadette D. Proctor, Jessica L. Semega, and Melissa A. Kollar. U.S. Census Bureau, September 2016. <www.census.gov>

Page 3: “The income and poverty estimates shown in this report are based solely on money income before taxes and do not include the value of noncash benefits, such as those provided by the Supplemental Nutrition Assistance Program (SNAP), Medicare, Medicaid, public housing, or employer-provided fringe benefits.”

Page 21:

Data on income collected in the ASEC [Current Population Survey Annual

Social and Economic Supplements] by the Census Bureau cover money income received (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, Medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive noncash benefits, such as Supplemental Nutrition Assistance/food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents, which often take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc. Data users should consider these elements when comparing income levels. Moreover, readers should be aware that for many different reasons there is a tendency in household surveys for respondents to underreport their income. Based on an analysis of independently derived income estimates, the Census Bureau determined that respondents report income earned from wages or salaries more accurately than other sources of income, and that the reported wage and salary income is nearly equal to independent estimates of aggregate income.

[282] Report: “Breadwinner Moms.” By Wendy Wang, Kim Parker, and Paul Taylor. Pew Research Center, May 29, 2013. <www.pewsocialtrends.org>

Page 1: “A record 40% of all households with children under the age of 18 include mothers who are either the sole or primary source of income for the family, according to a new Pew Research Center analysis of data from the U.S. Census Bureau. The share was just 11% in 1960.”

Page 4: “The share of never married mothers among all single mothers has increased from 4% in 1960 to 44% in 2011.”

Page 24: “The analysis of historical trends is based on microdata from the Decennial Censuses of 1960, 1970, 1980, 1990 and 2000 and the American Community Surveys (ACS) of 2010 and 2011. The microdata files were obtained from the IPUMS-USA database. Data are a 1% sample of the U.S. population for the five decennial censuses and ACS.”

[283] Dataset: “Table F-7. Type of Family, All Races by Median and Mean Income, 1947 to 2015.” U.S. Census Bureau, September 2016. <www2.census.gov>

NOTE: As detailed in the next footnote, the Census Bureau methodology for calculating median income estimates has changed over time. Use caution when comparing median household incomes for different years.

[284] Report: “Current Population Survey, 2016 Annual Social and Economic (ASEC) Supplement.” U.S. Census Bureau. Last updated January 2017. <www2.census.gov>

Page G-8:

Estimation of Median Incomes

The Census Bureau has changed the methodology for computing median income over time. The Census Bureau has computed medians using either Pareto interpolation or linear interpolation—depending on the size of the income interval—Pareto for intervals larger than $2,500 in width, linear otherwise. Currently, we are using linear interpolation to estimate all medians. Pareto interpolation assumes a decreasing density of population within an income interval, whereas linear interpolation assumes a constant density of population within an income interval. The Census Bureau calculated estimates of median income and associated standard errors for 1979 through 1987 using Pareto interpolation if the estimate was larger than $20,000 for people or $40,000 for families and households.

We calculated estimates of median income and associated standard errors for 1976, 1977, and 1978 using Pareto interpolation if the estimate was larger than $12,000 for people or $18,000 for families and households. This is because the width of the income interval containing the estimate is greater than $1,000. All other estimates of median income and associated standard errors for 1976 through 2014 (2015 CPS ASEC) and almost all of the estimates of median income and associated standard errors for 1975 and earlier were calculated using linear interpolation.

Thus, use caution when comparing median incomes above $12,000 for people or $18,000 for families and households for different years. Median incomes below those levels are more comparable from year to year since they have always been calculated using linear interpolation. For an indication of the comparability of medians calculated using Pareto interpolation with medians calculated using linear interpolation, see reference [5].

[285] Dataset: “Selected Characteristics of the Native and Foreign-Born Populations, 2015 American Community Survey 1-Year Estimates.” U.S. Census Bureau. Accessed June 7, 2017 at <factfinder.census.gov>

“Median earnings (dollars) for full-time, year-round workers … Total … Male [=] 49,938 … Female [=] 39,940”

CALCULATION: (49,938 – 39,940) / 49,938 = 20%

NOTE: The next footnote contains methodological details about this income data.

[286] Report: “Income and Poverty in the United States: 2015 (Current Population Reports).” By Bernadette D. Proctor, Jessica L. Semega, and Melissa A. Kollar. U.S. Census Bureau, September 2016. <www.census.gov>

Page 3:

The Census Bureau also reports income and poverty estimates based on data from the American Community Survey (ACS). The ACS is part of the 2020 Census program and eliminates the need for a long-form census questionnaire. …

The income and poverty estimates shown in this report are based solely on money income before taxes and do not include the value of noncash benefits, such as those provided by the Supplemental Nutrition Assistance Program (SNAP), Medicare, Medicaid, public housing, or employer-provided fringe benefits.

Page 21:

For each person 15 years and older in the sample, the Annual Social and Economic Supplement (ASEC) asks questions on the amount of money income received in the preceding calendar year from each of the following sources:

1. Earnings

2. Unemployment compensation

3. Workers’ compensation

4. Social security

5. Supplemental security income

6. Public assistance

7. Veterans’ payments

8. Survivor benefits

9. Disability benefits

10. Pension or retirement income

11. Interest

12. Dividends

13. Rents, royalties, and estates and trusts

14. Educational assistance

15. Alimony

16. Child support

17. Financial assistance from outside of the household

18. Other income

It should be noted that although the income statistics refer to receipts during the preceding calendar year, the demographic characteristics, such as age, labor force status, and household composition, are as of the survey date. The income of the household does not include amounts received by people who were members during all or part of the previous year if these people no longer resided in the household at the time of the interview. The ASEC collects income data for people who are current residents but did not reside in the household during the previous year.

Data on income collected in the ASEC [Current Population Survey Annual Social and Economic Supplements] by the Census Bureau cover money income received (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, Medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive noncash benefits, such as Supplemental Nutrition Assistance/food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents, which often take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc. Data users should consider these elements when comparing income levels. Moreover, readers should be aware that for many different reasons there is a tendency in household surveys for respondents to underreport their income. Based on an analysis of independently derived income estimates, the Census Bureau determined that respondents report income earned from wages or salaries more accurately than other sources of income, and that the reported wage and salary income is nearly equal to independent estimates of aggregate income.

[287] “State of the Union Address.” By President Barack Obama. White House, January 28, 2014. <obamawhitehouse.archives.gov>

Today, women make up about half our workforce. But they still make 77 cents for every dollar a man earns. That is wrong, and in 2014, it’s an embarrassment. A woman deserves equal pay for equal work. She deserves to have a baby without sacrificing her job. A mother deserves a day off to care for a sick child or sick parent without running into hardship—and you know what, a father does, too. It’s time to do away with workplace policies that belong in a “Mad Men” episode.

[288] Report: “An Analysis of Reasons for the Disparity in Wages Between Men and Women.” Prepared for the U.S. Department of Labor by CONSAD Research Corporation, January 12, 2009. <www.shrm.org>

Page 4: “In the political domain, the values calculated for the raw [gender wage] gap have been interpreted by many people as a clear indication of overt wage discrimination against women, and have been advanced as a justification for proposed policies mandating equal pay or comparable worth.”

[289] “American Time Use Survey—2015 Results.” U.S. Bureau of Labor Statistics, June 27, 2017. <www.bls.gov>

Page 4:

The estimates in this news release are based on annual average data from the American Time Use Survey (ATUS). The ATUS, which is conducted by the U.S. Census Bureau for the Bureau of Labor Statistics (BLS), is a continuous survey about how individuals age 15 and over spend their time. …

… In 2015, approximately 10,900 individuals were interviewed. …

ATUS sample households are chosen from the households that completed their eighth (final) interview for the Current Population Survey (CPS), the nation’s monthly household labor force survey. ATUS sample households are selected to ensure that estimates will be nationally representative.

One individual age 15 or over is randomly chosen from each sampled household. This “designated person” is interviewed by telephone once about his or her activities on the day before the interview—the “diary day.” …

ATUS designated persons are preassigned a day of the week about which to report. Preassignment is designed to reduce variability in response rates across the week and to allow oversampling of weekend days so that accurate weekend day measures can be developed. Interviews occur on the day following the assigned day. For example, a person assigned to report about a Monday would be contacted on the following Tuesday. Ten percent of designated persons are assigned to report about each of the five weekdays. Twenty-five percent are assigned to report about each weekend day. …

In the time diary portion of the ATUS interview, survey respondents sequentially report activities they did between 4 a.m. on the day before the interview until 4 a.m. on the day of the interview. For each activity, respondents are asked how long the activity lasted. For activities other than personal care activities (such as sleeping and grooming), interviewers also ask respondents where they were and who was in the room with them (if at home) or who accompanied them (if away from home). If respondents report doing more than one activity at a time, they are asked to identify which one was the “main” (primary) activity. If none can be identified, then the interviewer records the first activity mentioned. After completing the time diary, interviewers ask respondents additional questions to clearly identify work, volunteering, eldercare, and secondary childcare activities. Secondary childcare is defined as having a child under age 13 in one’s care while doing other activities. …

Average day. The average day measure reflects an average distribution across all persons in the reference population and all days of the week. The ATUS collects data about daily activities from all segments of the population age 15 and over, including persons who are employed and not employed.

Page 13:

Table 4. Employed persons working and time spent working on days worked by full- and part-time status and sex, jobholding status, educational attainment, and day of week, 2015 annual averages

Full-Time Workers

Sex

Percent of employed persons who worked on an average day

Average hours of work

Men

74.0

8.22

Women

69.8

7.84

CALCULATIONS:

  • (74.0 – 69.8) / 69.8 = 6%
  • (8.22 – 7.84) / 7.84 = 5%

[290] Study: “Majors by Gender: Is It Bias or the Major That Determines Future Pay?” By Katie Bardaro. PayScale, 2009. <www.payscale.com>

However, choice of degree type and college major play a large role in determining national pay differences across men and women. Simply put, women tend to choose majors that pay a lower national median pay. …

In an updated research project, we determined 15 common majors for men, 15 common majors for women and 15 common majors with roughly equal numbers of men and women graduates. Similar to AAUW, we find women tend to major in various Design/Art majors, Education, Nursing, and Public Relations, while men tend to major in Engineering, Finance, Computer Science, and Economics. Majors common to both include Accounting, Journalism, Biology, History, English and Mathematics.

Below are two tables detailing the common majors for each gender, the ratio of the specific gender, and the national median pay for those with the major who hold a bachelor’s degree and no higher degrees. (Note: The pay is NOT gender specific). …

As the above tables show, men are more likely to choose majors that lead to higher incomes. Only two majors common for women pay a national median pay over $60,000 (Nursing and Occupational Therapy), while 10 of the 15 common majors for men pay at least $60,000. The average pay across all of the common majors for men is $61,700, which is 35% higher than the average pay across the common female majors ($45,600).

[291] Report: “An Analysis of Reasons for the Disparity in Wages Between Men and Women.” Prepared for the U.S. Department of Labor by CONSAD Research Corporation, January 12, 2009. <www.shrm.org>

Page 6:

Because women have disproportionately worked in occupations with relatively low wages (e.g., teachers, nurses, secretaries, retail sales clerks) and men have disproportionately worked in occupations with comparatively high wages (e.g., executives, managers, doctors, lawyers, engineers, scientists), the average and median earnings of women in general has been much lower than the average and median earnings of men in general.

Many researchers have independently derived results in statistical analyses of different data sets that consistently indicate that the main factor accounting for the gender wage gap is differences between the occupations in which men and women typically work. [Boraas & Rodgers, 2003; Bowler, 1999; Fields & Wolff, 1995; Groshen, 1991; Johnson & Solon, 1986; Lowen & Sicilian, 2008; Oaxaca, 1973; Solberg & Laughlin, 1995; Weinberg, 2007]

[292] Study: “Graduating to a Pay Gap: The Earnings of Women and Men One Year after College Graduation.” By Christianne Corbett and Catherine Hill. Gender Pay Gap, American Association of University Women, 2012. <www.aauw.org>

Pages 1–2:

Men are more likely than women to major in fields like engineering and computer science, which typically lead to higher-paying jobs. Women are more likely than men to major in fields like education and the social sciences, which typically lead to lower-paying jobs. But college major is not the full story. One year after graduation, a pay gap exists between women and men who majored in the same field. Among business majors, for example, women earned just over $38,000, while men earned just over $45,000. Gender differences in college major only partially explain the pay gap.

Occupational factors also drive differences in pay. Although the choice of major is related to occupation, the relationship is not strict. For example, male engineering majors are more likely than their female counterparts to work as engineers after graduation. Women are more likely than men to work in business support and administrative assistance occupations and as teachers, social services professionals, and nurses and other health care providers one year after college graduation. Men are more likely than women to work in business and management occupations, computer and physical science occupations, and as engineers. The jobs that primarily employ men tend to pay more than the jobs that primarily employ women.

[293] Article: “Gender Wage Gap May Be Much Smaller Than Most Think.” By Natalia Kolesnikova and Yang Liu. The Regional Economist (published by the Federal Reserve Bank of St. Louis), October 2011. Pages 14–15. <www.stlouisfed.org>

Page 14:

Another important reason for the gender gap is the difference in labor force attachment between men and women. Women are likely to leave their careers temporarily for childbirth and raising children. Such leaves may be associated with a decrease in human capital and with temporary delays in training and promotion, which consequently lead to lower wages.

[294] Report: “An Analysis of Reasons for the Disparity in Wages Between Men and Women.” Prepared for the U.S. Department of Labor by CONSAD Research Corporation, January 12, 2009. <www.shrm.org>

Page 8:

Many researchers have investigated the relationship between workers’ earnings and their cumulative work experience (measured as their estimated total number of years of employment) or their tenure on their current jobs (measured as the years of employment by the current employer without interruption by work for another employer). [Blau & Kahn, 2006; Boraas & Rodgers, 2003; Gabriel, 2005; Light & Ureta, 1995; U.S. Government Accounting Office (GAO), 2003 (since renamed U.S. Government Accountability Office)] In particular, Blau and Kahn (2006) report that results from their statistical analysis indicate that women’s gains in work experience during the 1980s account for about one third of the total narrowing of the gender wage gap over that time.

Page 9:

The wages paid to workers are affected not only by the amount of work experience that a worker has accumulated, but also by the continuity of the accumulation. Results from a statistical analysis of the earnings patterns of male and female college graduates over time indicate that leave taken from a career, such as leave for childbirth or for raising children, is associated with reduced income, and that such interruptions are much more prevalent among mothers than among fathers. [Dey & Hill, 2007] …

Examining the reductions in earnings that have been observed after career interruptions that have lasted at least one year, Light and Ureta (1995) have found that the estimated decrease in earnings upon returning to work is 25 percent among men and 23 percent among women. They further have estimated that the decrease is quite transitory, and that recovery is quicker among women than among men. Four years after returning to work, the earnings of women who have taken extended leave are almost the same as the earnings of their continuously employed counterparts; whereas the earnings of men who have taken extended leave take slightly longer than that to achieve such parity.

[295] Paper: “The Gender Pay Gap, Fringe Benefits, and Occupational Crowding.” By Eric Solberg and Teresa Laughlin. Industrial Labor Relations Review, July 1, 1995. Pages 692–708. <journals.sagepub.com>

Page 706:

Our analysis of the gender pay gap is the first to include fringe benefits in a comprehensive measure of compensation for men and women. The results show that including fringe benefits makes a considerable difference in the analysis of earnings differentials. In fact, we conclude that any measure of earnings that excludes fringe benefits may produce misleading results as to the existence, magnitude, consequence, and source of market discrimination. For our sample of working men and women between the ages of 26 and 34 in 1990, the average female wage rate was 87.4% of the average male wage rate; but when an index of total compensation is used, the estimate rises to 96.4% of male compensation. Almost surely the use of the wage rate alone overstates the gap.

[296] Report: “An Analysis of Reasons for the Disparity in Wages Between Men and Women.” Prepared for the U.S. Department of Labor by CONSAD Research Corporation, January 12, 2009. <www.shrm.org>

Page 11:

Wages and salaries are complex prices. They are payments made to workers to compensate them for performing the duties and accepting the working conditions of their jobs. They are one of the major inducements used by employers to attract and retain desired workers. …

Thus, to attract and retain workers, employers that do not provide a fringe benefit such as health insurance will need to pay wages that are sufficiently higher than those paid by otherwise comparable competitors that do provide the fringe benefit that workers choose to work for them despite the lack of the fringe benefit.

[297] Paper: “A Meta-Analysis of Sex Differences in Physical Ability: Revised Estimates and Strategies for Reducing Differences in Selection Contexts.” By Stephen H. Courtright and others. Journal of Applied Psychology, June 3, 2013. Pages 623–641. <psycnet.apa.org>

Page 623:

Physically demanding occupations make up a significant share of most labor markets globally. For example, over 28% of the U.S. labor force works in physically demanding occupations such as public safety, construction, maintenance and repair, and the military (Bureau of Labor Statistics, 2011). In such occupations, physical ability tests are widely used as tools for selection, placement, and retention decisions…. The importance of physical ability tests is difficult to overstate given that workers who fail to meet job-related physical demands have lower performance, more injuries, more absenteeism, and higher mortality rates (Gebhardt & Baker, 2010a; Hogan, 1991a). Moreover, since low performance in many physically demanding jobs can have catastrophic consequences (e.g., public safety; Colquitt, LePine, Zapata, & Wild, 2011), physical ability tests go beyond just benefitting organizations to benefitting society as a whole (Gebhardt & Baker, 2007).

… The driving force of this controversy is the large male–female differences that exist on certain physical abilities. In fact, scholars have suggested that sex differences on certain physical abilities are larger than any other subgroup difference found on any other human ability or characteristic relevant to personnel selection….

Page 633: “Regarding the first contribution, our study shows that large sex differences exist for muscular strength and cardiovascular endurance abilities. However, no significant sex differences exist for movement quality ability.”

Page 636: “As physically demanding occupations continue to hold an important role in labor economies globally and as more women enter physically demanding occupations, we hope our study will be useful to researchers and practitioners who seek to investigate ways to leverage the validity of physical ability tests while employing evidence-based strategies for potentially reducing sex differences on such tests.”

[298] Paper: “Structure of Physical Performance in Occupational Tasks.” By Joyce Hogan. Journal of Applied Psychology, 1991. Pages 495–507. <psycnet.apa.org>

Page 496:

The new research on the physical requirements of occupational tasks can be applied to physical tests for employee selection. Few personnel selection issues are as problematic as those involving physical standards (Hogan & Quigley, 1986). Generally, this is because physical performance tests—especially strength and endurance measures—tend to screen out proportionally more women and some ethnic-group members than White men.

Many physically demanding occupational tasks require multidimensional job-analysis methods. Consider a firefighter spraying a burning structure with a charged firehose. The task requires strength to resist the backpressure of the charged hose, endurance to handle the hose for extended periods of time, and, perhaps, balance if the footing is slippery or if the firefighter must work from a ladder. The categories of task evaluation must accommodate a variety of physical requirements.

[299] Study: “Graduating to a Pay Gap: The Earnings of Women and Men One Year after College Graduation.” By Christianne Corbett and Catherine Hill. Gender Pay Gap, American Association of University Women, 2012. <www.aauw.org>

Page 7: “This report examines the pay gap between men and women working full time in 2009, just one year after college graduation in 2007–08. We limited our analysis to full-time workers to make a valid comparison of earnings.”

Page 8:

Analyzing the gender pay gap among college graduates at the beginning of their careers provides valuable insight. Most are young (23 years old, on average), are relatively inexperienced in the workplace, have never been married, and are not raising children. The broad similarities in the lives of men and women at this time set the stage for a solid comparison. …

… This nationally representative sample represents all individuals who earned their first bachelor’s degree between July 1, 2007, and June 30, 2008, by age 35 or younger at institutions eligible for federal financial aid (Title IV-eligible institutions) in the United States and Puerto Rico.

Page 21: “That is, after we controlled for all the factors included in our analysis that we found to affect earnings, college-educated women working full time earned an unexplained 7 percent less than their male peers did one year out of college (see figure 10; see also figure 13 in the appendix).”

[300] Study: “Majors by Gender: Is It Bias or the Major That Determines Future Pay?” By Katie Bardaro. PayScale, 2009. <www.payscale.com>

Controlling allows us to perform an “apples to apples” comparison of men and women: all differences in responsibility, experience, education, etc., are taken into account, so that the controlled female median pay represents exactly the same set of qualifications as the controlled male median pay. …

Once we control for outside factors the wage gap between men and women shrinks considerably. Now women earn typical pay that is on average 98% of the typical pay for men by major. Occasionally, women may even earn more. Therefore, when looking at gender-specific pay by major for a controlled sample, the wage gap all but disappears.

The above data goes to show that major choice is a key reason for the gender wage gap of 77 cents to the dollar. In other words, women tend to choose majors (and thus jobs) that pay less on average. However, these majors pay less to both men and women.

[301] Paper: “The Gender Pay Gap, Fringe Benefits, and Occupational Crowding.” By Eric Solberg and Teresa Laughlin. Industrial Labor Relations Review, July 1, 1995. Pages 692–708. <journals.sagepub.com>

Page 692: “Using data from the 1991 National Longitudinal Survey of Youth, the authors estimate earnings equations for each of seven occupational categories and the aggregate sample.”

Page 706:

Our analysis of the gender pay gap is the first to include fringe benefits in a comprehensive measure of compensation for men and women. The results show that including fringe benefits makes a considerable difference in the analysis of earnings differentials. In fact, we conclude that any measure of earnings that excludes fringe benefits may produce misleading results as to the existence, magnitude, consequence, and source of market discrimination. For our sample of working men and women between the ages of 26 and 34 in 1990, the average female wage rate was 87.4% of the average male wage rate; but when an index of total compensation is used, the estimate rises to 96.4% of male compensation. Almost surely the use of the wage rate alone overstates the gap.

[302] Report: “An Analysis of Reasons for the Disparity in Wages Between Men and Women.” Prepared for the U.S. Department of Labor by CONSAD Research Corporation, January 12, 2009. <www.shrm.org>

Page 15:

Extant economic research has identified numerous factors that contribute to the gender wage gap. Many of the factors relate to differences in the choices and behavior of women and men in balancing their work, personal, and family lives. These factors include, most notably, the occupations and industries in which they work, and their human capital development, work experience, career interruptions, and motherhood. Other factors are sources of wage adjustments that compensate specific groups of workers for benefits or duties that disproportionately impact them. Such factors for which empirical evidence has been developed include health insurance, other fringe benefits, and overtime work.

It is not possible to produce a reliable quantitative estimate of the aggregate portion of the raw gender wage gap for which the explanatory factors that have been identified account. Nevertheless, it can confidently be concluded that, collectively, those factors account for a major portion and, possibly, almost all of the raw gender wage gap.

[303] Dataset: “2015 Median Household Income by Marital Status, Race, and Hispanic Origin.” U.S. Census Bureau. Accessed January 24, 2017 at <www.census.gov>

[304] Webpage: “Current Population Survey (CPS) Respondents.” U.S. Census Bureau. Last updated September 23, 2011. <www.bls.gov>

The Current Population Survey (CPS) is a monthly survey of households conducted by the Census Bureau for the Bureau of Labor Statistics. In addition to the national unemployment rate, it provides a comprehensive body of data on the labor force, employment, unemployment, the unemployment rate, persons not in the labor force, hours of work, earnings, and other demographic and labor force characteristics. …

You will be interviewed at your home or over the telephone by a Census Bureau employee. The survey is not conducted by mail, e-mail, or online. …

… Any household member 15 years of age or older can respond for the household. However, we would like to talk to someone who is knowledgeable about people in the household.

[305] Document: “Basic CPS Questionnaire, Labor Force Items.” U.S. Census Bureau, July 8, 2011. <www2.census.gov>

Page 25:

Which category represents (your/name of reference person/the total combined income) (total combined income during the past 12 months?/ of all members of your FAMILY during the past 12 months?/ of all members of (name of reference person) ‘s FAMILY during the past 12 months?)

This includes money from jobs, net income from business, farm or rent, pensions, dividends, interest, social security payments and any other money income received (. / by members of (your/ name of reference person) FAMILY who are 15 years of age or older.)

[306] Report: “Income and Poverty in the United States: 2015 (Current Population Reports).” By Bernadette D. Proctor, Jessica L. Semega, and Melissa A. Kollar. U.S. Census Bureau, September 2016. <www.census.gov>

Page 3: “The income and poverty estimates shown in this report are based solely on money income before taxes and do not include the value of noncash benefits, such as those provided by the Supplemental Nutrition Assistance Program (SNAP), Medicare, Medicaid, public housing, or employer-provided fringe benefits.”

Page 21:

Data on income collected in the ASEC [Current Population Survey Annual

Social and Economic Supplements] by the Census Bureau cover money income received (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, Medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive noncash benefits, such as Supplemental Nutrition Assistance/food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents, which often take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc. Data users should consider these elements when comparing income levels. Moreover, readers should be aware that for many different reasons there is a tendency in household surveys for respondents to underreport their income. Based on an analysis of independently derived income estimates, the Census Bureau determined that respondents report income earned from wages or salaries more accurately than other sources of income, and that the reported wage and salary income is nearly equal to independent estimates of aggregate income.

[307] Dataset: “2015 Educational Attainment of 25–65-Year-Olds, by Race, and Hispanic Origin.” U.S. Census Bureau. Accessed February 27, 2017 at <www.census.gov>

[308] Webpage: “Current Population Survey (CPS) Respondents.” U.S. Census Bureau. Last updated September 23, 2011. <www.bls.gov>

The Current Population Survey (CPS) is a monthly survey of households conducted by the Census Bureau for the Bureau of Labor Statistics. In addition to the national unemployment rate, it provides a comprehensive body of data on the labor force, employment, unemployment, the unemployment rate, persons not in the labor force, hours of work, earnings, and other demographic and labor force characteristics. …

You will be interviewed at your home or over the telephone by a Census Bureau employee. The survey is not conducted by mail, e-mail, or online. …

… Any household member 15 years of age or older can respond for the household. However, we would like to talk to someone who is knowledgeable about people in the household.

[309] Dataset: “2015 Median Earnings of Adult Civilian Persons Aged 25 to 65 by Educational Attainment, Race, Hispanic Origin, Nativity, and Marital Status.” U.S. Census Bureau. Accessed February 27, 2017 at <www.census.gov>

[310] Webpage: “Current Population Survey (CPS) Respondents.” U.S. Census Bureau. Last updated September 23, 2011. <www.bls.gov>

The Current Population Survey (CPS) is a monthly survey of households conducted by the Census Bureau for the Bureau of Labor Statistics. In addition to the national unemployment rate, it provides a comprehensive body of data on the labor force, employment, unemployment, the unemployment rate, persons not in the labor force, hours of work, earnings, and other demographic and labor force characteristics. …

You will be interviewed at your home or over the telephone by a Census Bureau employee. The survey is not conducted by mail, e-mail, or online. …

… Any household member 15 years of age or older can respond for the household. However, we would like to talk to someone who is knowledgeable about people in the household.

[311] Document: “Basic CPS Questionnaire, Labor Force Items.” U.S. Census Bureau, July 8, 2011. <www2.census.gov>

Page 25:

Which category represents (your/name of reference person/the total combined income) (total combined income during the past 12 months?/ of all members of your FAMILY during the past 12 months?/ of all members of (name of reference person) ‘s FAMILY during the past 12 months?)

This includes money from jobs, net income from business, farm or rent, pensions, dividends, interest, social security payments and any other money income received (. / by members of (your/ name of reference person) FAMILY who are 15 years of age or older.)

[312] Report: “Income and Poverty in the United States: 2015 (Current Population Reports).” By Bernadette D. Proctor, Jessica L. Semega, and Melissa A. Kollar. U.S. Census Bureau, September 2016. <www.census.gov>

Page 3: “The income and poverty estimates shown in this report are based solely on money income before taxes and do not include the value of noncash benefits, such as those provided by the Supplemental Nutrition Assistance Program (SNAP), Medicare, Medicaid, public housing, or employer-provided fringe benefits.”

Page 21:

Data on income collected in the ASEC [Current Population Survey Annual

Social and Economic Supplements] by the Census Bureau cover money income received (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, Medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive noncash benefits, such as Supplemental Nutrition Assistance/food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents, which often take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc. Data users should consider these elements when comparing income levels. Moreover, readers should be aware that for many different reasons there is a tendency in household surveys for respondents to underreport their income. Based on an analysis of independently derived income estimates, the Census Bureau determined that respondents report income earned from wages or salaries more accurately than other sources of income, and that the reported wage and salary income is nearly equal to independent estimates of aggregate income.

[313] Dataset: “2015 Persons by Kind of Family, Race, and Hispanic Origin.” Accessed July 24, 2017 at <www.census.gov>

[314] Webpage: “Current Population Survey (CPS) Respondents.” U.S. Census Bureau. last updated September 23, 2011. <www.bls.gov>

The Current Population Survey (CPS) is a monthly survey of households conducted by the Census Bureau for the Bureau of Labor Statistics. In addition to the national unemployment rate, it provides a comprehensive body of data on the labor force, employment, unemployment, the unemployment rate, persons not in the labor force, hours of work, earnings, and other demographic and labor force characteristics. …

You will be interviewed at your home or over the telephone by a Census Bureau employee. The survey is not conducted by mail, e-mail, or online. …

… Any household member 15 years of age or older can respond for the household. However, we would like to talk to someone who is knowledgeable about people in the household.

[315] Dataset: “2015 Median Household Income by Marital Status, Race, and Hispanic Origin.” U.S. Census Bureau. Accessed April 27, 2017 at <www.census.gov>

NOTES:

  • An Excel file containing the data is available upon request.
  • The next two footnotes contain methodological details about this data.

[316] Webpage: “Current Population Survey (CPS) Respondents.” U.S. Census Bureau. Last updated September 23, 2011. <www.bls.gov>

The Current Population Survey (CPS) is a monthly survey of households conducted by the Census Bureau for the Bureau of Labor Statistics. In addition to the national unemployment rate, it provides a comprehensive body of data on the labor force, employment, unemployment, the unemployment rate, persons not in the labor force, hours of work, earnings, and other demographic and labor force characteristics. …

You will be interviewed at your home or over the telephone by a Census Bureau employee. The survey is not conducted by mail, e-mail, or online. …

… Any household member 15 years of age or older can respond for the household. However, we would like to talk to someone who is knowledgeable about people in the household.

[317] Document: “Basic CPS Questionnaire, Labor Force Items.” U.S. Census Bureau, July 8, 2011. <www2.census.gov>

Page 25:

Which category represents (your/name of reference person/the total combined income) (total combined income during the past 12 months?/ of all members of your FAMILY during the past 12 months?/ of all members of (name of reference person) ‘s FAMILY during the past 12 months?)

This includes money from jobs, net income from business, farm or rent, pensions, dividends, interest, social security payments and any other money income received (. / by members of (your/ name of reference person) FAMILY who are 15 years of age or older.)

[318] Report: “Income and Poverty in the United States: 2015 (Current Population Reports).” By Bernadette D. Proctor, Jessica L. Semega, and Melissa A. Kollar. U.S. Census Bureau, September 2016. <www.census.gov>

Page 3: “The income and poverty estimates shown in this report are based solely on money income before taxes and do not include the value of noncash benefits, such as those provided by the Supplemental Nutrition Assistance Program (SNAP), Medicare, Medicaid, public housing, or employer-provided fringe benefits.”

Page 21:

Data on income collected in the ASEC [Current Population Survey Annual

Social and Economic Supplements] by the Census Bureau cover money income received (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, Medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive noncash benefits, such as Supplemental Nutrition Assistance/food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents, which often take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc. Data users should consider these elements when comparing income levels. Moreover, readers should be aware that for many different reasons there is a tendency in household surveys for respondents to underreport their income. Based on an analysis of independently derived income estimates, the Census Bureau determined that respondents report income earned from wages or salaries more accurately than other sources of income, and that the reported wage and salary income is nearly equal to independent estimates of aggregate income.

[319] Dataset: “2015 Median Family Income by Detailed Nativity and Hispanic Origin.” U.S. Census Bureau. Accessed June 5, 2017 at <www.census.gov>

[320] Report: “Income and Poverty in the United States: 2015 (Current Population Reports).” By Bernadette D. Proctor, Jessica L. Semega, and Melissa A. Kollar. U.S. Census Bureau, September 2016. <www.census.gov>

Page 3: “The income and poverty estimates shown in this report are based solely on money income before taxes and do not include the value of noncash benefits, such as those provided by the Supplemental Nutrition Assistance Program (SNAP), Medicare, Medicaid, public housing, or employer-provided fringe benefits.”

Page 21:

For each person 15 years and older in the sample, the Annual Social and Economic Supplement (ASEC) asks questions on the amount of money income received in the preceding calendar year from each of the following sources:

1. Earnings

2. Unemployment compensation

3. Workers’ compensation

4. Social security

5. Supplemental security income

6. Public assistance

7. Veterans’ payments

8. Survivor benefits

9. Disability benefits

10. Pension or retirement income

11. Interest

12. Dividends

13. Rents, royalties, and estates and trusts

14. Educational assistance

15. Alimony

16. Child support

17. Financial assistance from outside of the household

18. Other income

It should be noted that although the income statistics refer to receipts during the preceding calendar year, the demographic characteristics, such as age, labor force status, and household composition, are as of the survey date. The income of the household does not include amounts received by people who were members during all or part of the previous year if these people no longer resided in the household at the time of the interview. The ASEC collects income data for people who are current residents but did not reside in the household during the previous year.

Data on income collected in the ASEC [Current Population Survey Annual Social and Economic Supplements] by the Census Bureau cover money income received (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, Medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive noncash benefits, such as Supplemental Nutrition Assistance/food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents, which often take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc. Data users should consider these elements when comparing income levels. Moreover, readers should be aware that for many different reasons there is a tendency in household surveys for respondents to underreport their income. Based on an analysis of independently derived income estimates, the Census Bureau determined that respondents report income earned from wages or salaries more accurately than other sources of income, and that the reported wage and salary income is nearly equal to independent estimates of aggregate income.

[321] Report: “The Economic and Fiscal Consequences of Immigration.” By the National Academies of Sciences, Engineering and Medicine, Division of Behavioral and Social Sciences and Education, Committee on National Statistics, Panel on the Economic and Fiscal Consequences of Immigration. Edited by Francine D. Blau and Christopher Mackie. National Academies Press, September 22, 2016. <www.nap.edu>

Pages 85–87:

Following Borjas (2016a), the panel investigated the rate of economic assimilation by calculating age-adjusted wage differentials between each immigrant cohort and its native-born cohort, using a regression estimated separately for each year—1970, 1980, 1990, 2000, and 2010–2012—from the Decennial Census and ACS IPUMS data. The dependent variable is the log of weekly earnings, and the regressors initially include age (introduced as a third-order polynomial, or cubic term) and arrival-cohort fixed effects, and then education as a third regressor.10 Tables 3-12 and 3-13 show how the wages of immigrants relative to native-born workers of the same age evolve with time in the United States, computed separately for different immigrant arrival cohorts.11 Male immigrants who arrived between 1965 and 1969 began with an initial wage disadvantage of 23.5 percent, but the gap narrowed to 12 percent 10 years after arrival. By 40 years after arrival, this immigrant arrival cohort earned 17.6 percent more per week than comparable native-born males. Later-arriving cohorts began with a larger wage disadvantage: 31.4 percent lower than native-born males for those admitted between 1975 and 1979, 33.1 percent lower for those admitted between 1985 and 1989, and 27.3 percent lower for those admitted between 1995 and 1999. Moreover, the wage disadvantage does not disappear for these arrival cohorts, and the rate at which it narrows has slowed. For example, the 1965 cohort made up 21.5 percentage points of the gap in their first 20 years, whereas the 1975 cohort made up only 13.8 percentage points and the 1985 cohort only 7.9 percentage points.

When the panel additionally controlled for education, which allows for comparison of the degree to which immigrants catch up with their native-born peers with similar skills, the sizes of the immigrant-to-native-born wage gaps are much reduced. Moreover, it is only the two most recent arrival cohorts that have not yet closed the gap with their native-born peers with the same education. Of these two cohorts, 1985–89 arrivals have nearly closed the gap after 20 years in the United States, earning only 2.6 percent less than natives with the same education.

Since immigrants are disproportionately low-skilled, it is also likely that growing wage inequality in the economy generally, which is associated with a widening wage gap between high- and low-skilled workers, has adversely affected immigrant entry wages and impeded their capacity to catch up to natives. Putting this somewhat differently, even if immigrant skills had remained constant, their wages relative to natives would have fallen. Borjas (1995a) examined relative wages during the 1980s (a time when low-skilled immigrant workers fared particularly poorly) and found that, although the change in wage structure accounted for some (16–17%) of the decline in the relative wages of immigrants, most of it remained and was attributable to declining educational attainment relative to natives.12 A larger role for wage structure was obtained by Butcher and DiNardo (1998). They analyzed the role of the changing wage structure in the native-immigrant wage gap by estimating wage distributions of male and female immigrants who were recent arrivals in 1970, simulating what would have happened had they faced the wage structure obtaining in 1990. The counterfactual analysis allowed the researchers to tease out how much of the gap in native-immigrant wage distribution could be attributed to changing immigrant skills versus change in the wage structure. Depending on where a worker was along the wage distribution, the wage structure was found to have dramatic effects. For male workers at the higher end of the distribution, the wage structure changes explained 68 percent of the increase in wage gap.

The following key conclusions can be drawn from the above analyses. As their time spent in the United States lengthened, male immigrants who arrived between 1965 and 1969 experienced rapid relative growth in their wages, which allowed them to close the gap with natives. This indication of economic integration has slowed somewhat in more recent decades; the aging profile for relative wages has flattened across arrival cohorts, indicating a slowing rate of wage convergence for immigrants admitted after 1979. These overall conclusions hold after controlling for immigrants’ educational attainment, although the relative wage picture for immigrants is considerably more favorable when education is controlled for.

Compared to male immigrants of the same cohort, female immigrants start off with a less dramatic wage disadvantage, particularly if earlier cohorts are considered, but they experience slower growth in their wages relative to their native-born than do male immigrants (compare Tables 3-12 and 3-13). The 1995–99 arrival cohort did not experience any relative wage growth during its first 10 years in the United States. Much of the wage disadvantage of female immigrants disappears, however, when years of education are accounted for (lower half of Table 3-13), indicating that education differences explain much of the wage difference for immigrant women compared with native-born women. Even the large wage disadvantage for the 1995–99 cohort is mostly accounted for by that group’s lesser educational attainment compared with native-born females. Recent trends in part reflect increasing rates of inflow of Mexican immigrants with low education during the 1990s (Borjas, 2014b).

Table 3-12. Weekly Wage Assimilation of Male Immigrants, by Cohort (Percentage Difference between Native-born and Foreign born Wages)

Controlling for Age (Cubic) Only

Arrival Cohort

Years Since Migration

0

10

20

30

40

1965–69 Arrivals

–0.235

–0.12

–0.02

–0.014

0.176

1975–79 Arrivals

–0.314

–0.185

–0.176

–0.136

1985–89 Arrivals

–0.331

–0.269

–0.252

1995–99 Arrivals

–0.273

–0.269

10 Age is introduced as a third order polynomial to control for nonlinear effects of age on earnings.

[322] Report: “The Economic and Fiscal Consequences of Immigration.” By the National Academies of Sciences, Engineering and Medicine, Division of Behavioral and Social Sciences and Education, Committee on National Statistics, Panel on the Economic and Fiscal Consequences of Immigration. Edited by Francine D. Blau and Christopher Mackie. National Academies Press, September 22, 2016. <www.nap.edu>

Pages 85–86:

Following Borjas (2016a), the panel investigated the rate of economic assimilation by calculating age-adjusted wage differentials between each immigrant cohort and its native-born cohort, using a regression estimated separately for each year—1970, 1980, 1990, 2000, and 2010–2012—from the Decennial Census and ACS IPUMS data. The dependent variable is the log of weekly earnings, and the regressors initially include age (introduced as a third-order polynomial, or cubic term) and arrival-cohort fixed effects, and then education as a third regressor.

Page 87: “Table 3-12. Weekly Wage Assimilation of Male Immigrants, by Cohort (Percentage Difference between Native-born and Foreign born Wages)”

[323] Calculated with data from the report: “A Description of the Immigrant Population—2013 Update.” Congressional Budget Office, May 8, 2013. <www.cbo.gov>

Page 13 (of PDF): “Exhibit 11. Educational Attainment of People Ages 25 to 64, by Birthplace, 2012 (Percent) … Source: Congressional Budget Office based on monthly data from Census Bureau, Current Population Survey, Outgoing Rotation Groups, 2012, <www.census.gov>. … [Oceania] includes Australia, New Zealand, and the Pacific Islands.”

NOTE: An Excel file containing the data and calculations is available upon request.

[324] Report: “Investing in English Skills: The Limited English Proficient Workforce in U.S. Metropolitan Areas.” By Jill H. Wilson. Brookings Institution, September 2014. <www.brookings.edu>

Page 1:

• Nearly one in 10 working-age U.S. adults—19.2 million persons aged 16 to 64—is considered limited English proficient. Two-thirds of this population speaks Spanish, but speakers of Asian and Pacific Island languages are most likely to be LEP. The vast majority of working-age LEP adults are immigrants, and those who entered the United States more recently are more likely to be LEP.

• Working-age LEP adults earn 25 to 40 percent less than their English proficient counterparts. While less educated overall than English proficient adults, most LEP adults have a high school diploma, and 15 percent hold a college degree. LEP workers concentrate in low-paying jobs and different industries than other workers.

[325] Article: “What Causes a Country’s Standard of Living to Rise?” By Ana Maria Santacreu. Federal Reserve Bank of St. Louis, December 28, 2015. <www.stlouisfed.org>

One way to measure the improvement in the living standards of a country is by looking at the growth rate of its gross domestic product (GDP) per capita. …

As an example, Turkey’s labor utilization grew around 4 percent in 2014, whereas it experienced a drop in labor productivity of about 2 percent. These numbers imply that the improvement in living standards in Turkey—as measured by GDP per capita, which increased by 2 percent—was mainly driven by an increase in labor utilization.

A similar pattern emerges for Korea, New Zealand, Portugal and Iceland. All these countries experienced positive growth in their living standards driven mainly by an increase in the number of hours per capita, as labor productivity decreased in all these countries.

[326] Report: “Valuing Non-Market Work.” By Nancy Folbre. United Nations, Human Development Report Office, 2015. <hdr.undp.org>

Page 3: “The unpaid time that people devote to the care of family, friends and neighbours clearly contributes to economic living standards, social well-being and the development of human capabilities. … It is difficult to estimate the market value of non-market work, and it is important to remember that not all of its contributions can be measured in market terms.”

[327] Book: For Love or Money. Edited by Nancy Folbre. Russell Sage Foundation, 2012. Chapter 5: “Valuing Care. By Nancy Folbre. Pages 92–111.

Page 105:

One early study estimated the value of unpaid personal assistance to adults with disabilities at $168 billion in 1996, compared to $32 billion spent on paid personal assistance (LaPlante, Harrington, and Kang 2002). …

A recent study offering state-by-state estimates of the value of family care-giving in 2004 uses a replacement-cost approach, applying an average of the minimum wage at the time ($5.15 an hour) and the average national wage rate for home health aides and other workers in the home health industry ($14.68), which comes to $9.92 per hour (Arno, Levine, and Memmnott 1999; NFCA/FCA 2006). A review of five different estimates that projected these to the U.S. population in 2006 found that the annual economic value of unpaid caregiving for adults was about $354 billion, more than total public spending on Medicaid and far higher than total spending on nursing home and home health care (Gibson and Houser 2007). A recent estimate published by the American Association of Retired Persons (AARP) based on 2009 data put the total value of unpaid care for adults at $450 billion, more than twice the total of paid long-term care services from all sources (Feinberg et al. 2011).

[328] Book: Income Inequality: Economic Disparities and the Middle Class in Affluent Countries. Edited by Janet C. Gornick and Markus Jantti. Stanford University Press, 2013. Chapter 8: “Women’s Employment, Unpaid Work, and Economic Inequality.” By Nancy Folbre, Janet C. Gornick, Helen Connolly, and Teresa Munzi. Pages 234–260.

Page 256:

The impact of declining levels of unpaid work over time on all aspects of household living standards deserves more careful consideration. There is something fundamentally misleading about measuring gains to family earnings provided by increases in women’s employment that do not account for the reduction in living standards resulting from declines in time devoted to unpaid work.

[329] Calculated with data from:

a) Dataset: “Table A-13. Employment Status of the Civilian Noninstitutional Population by Age, Sex, and Race.” U.S. Department of Labor, Bureau of Labor Statistics. Last updated August 4, 2017. <www.bls.gov>

b) Dataset: “Table A-18. Employed and Unemployed Full and Part-Time Workers by Age, Sex, Race, and Hispanic or Latino Ethnicity.” U.S. Department of Labor, Bureau of Labor Statistics. Last updated August 4, 2017. <www.bls.gov>

c) Dataset: “Monthly Population Estimates for the United States: April 1, 2010 to December 1, 2017 (NA-EST2016-01).”, U.S. Census Bureau, Population Division, December 2016. <www2.census.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[330] Calculated with data from:

a) Dataset: “Table A-13. Employment Status of the Civilian Noninstitutional Population by Age, Sex, and Race.” U.S. Department of Labor, Bureau of Labor Statistics. Last updated August 4, 2017. <www.bls.gov>

b) Dataset: “Table A-18. Employed and Unemployed Full and Part-Time Workers by Age, Sex, Race, and Hispanic or Latino Ethnicity.” U.S. Department of Labor, Bureau of Labor Statistics. Last updated August 4, 2017. <www.bls.gov>

c) Dataset: “Monthly Population Estimates for the United States: April 1, 2010 to December 1, 2017 (NA-EST2016-01).”, U.S. Census Bureau, Population Division, December 2016. <www2.census.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[331] Calculated with data from:

a) Dataset: “Table A-13. Employment Status of the Civilian Noninstitutional Population by Age, Sex, and Race.” U.S. Department of Labor, Bureau of Labor Statistics. Last updated August 4, 2017. <www.bls.gov>

b) Dataset: “Table A-18. Employed and Unemployed Full and Part-Time Workers by Age, Sex, Race, and Hispanic or Latino Ethnicity.” U.S. Department of Labor, Bureau of Labor Statistics. Last updated August 4, 2017. <www.bls.gov>

c) Dataset: “Monthly Population Estimates for the United States: April 1, 2010 to December 1, 2017 (NA-EST2016-01).”, U.S. Census Bureau, Population Division, December 2016. <www2.census.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[332] “Report on the Economic Well-Being of U.S. Households in 2015.” Board of Governors of the Federal Reserve System, May 2016. <www.federalreserve.gov>

Page 1: “Twenty-two percent of employed adults indicate that they are either working multiple jobs, doing informal work for pay in addition to their main job, or both.”

Page 69:

The Survey of Household Economic Decisionmaking (SHED) was designed by Board staff and administered by GfK, an online consumer research company, on behalf of the Board. In order to create a nationally representative probability-based sample, GfK’s KnowledgePanel selected respondents based on both random digit dialing and address-based sampling (ABS). Since 2009, new respondents have been recruited using ABS. To recruit respondents, GfK sends out mailings to a random selection of residential postal addresses. Out of 100 mailings, approximately 14 households contact GfK and express an interest in joining the panel. Of those who contact GfK, three-quarters complete the process and become members of the panel.51 If the person contacted is interested in participating but does not have a computer or Internet access, GfK provides him or her with a laptop and access to the Internet. Panel respondents are continuously lost to attrition and added to replenish the panel, so the recruitment rate and enrollment rate may vary over time.

… A total of 8,681 KnowledgePanel members received e-mail invitations to complete this survey, including an oversample of respondents with a household income under $40,000. The sample included a random selection of 2,853 out of the 4,262 KnowledgePanel respondents who participated in the Board’s 2014 SHED (excluding those who were in the 2014 lower-income oversample) and an additional 3,332 randomly selected KnowledgePanel respondents who did not participate in the Board’s previous survey. It also included 2,496 randomly selected KnowledgePanel respondents whose household income was under $40,000. (See table 1 in main text.) The lower-income oversample was included in the study to ensure sufficient coverage of this population for key questions of interest.

From these three components of the sample, a total of 5,695 people (excluding breakoffs, speeders, and bulk non-responders) responded to the e-mail request to participate and completed the survey yielding a final stage completion rate of 65.5 percent. The recruitment rate for the primary sample, reported by GfK, was 13.5 percent and the profile rate was 64.3 percent, for a cumulative response rate of 5.7 percent.

51 For further details on the KnowledgePanel® sampling methodology and comparisons between KnowledgePanel® and telephone surveys, see www.knowledgenetworks.com/accuracy/spring2010/disogra-spring10.html.

[333] Report: “Factors Affecting the Labor Force Participation of People Ages 25 to 54.” Congressional Budget Office, February 2018. <www.cbo.gov>

Page 4:

Labor force participation is an important component of economic growth: As more people participate in the labor force, firms are able to expand employment and increase production. CBO estimates that growth in potential (that is, maximum sustainable) output over the next decade will be faster than it has been since the 2007–2009 recession, in part because of the projected stability—after a sustained decline—of the labor force participation rate for people ages 25 to 54. (However, that growth in potential output is projected to be slower than the average growth over the 1980s, 1990s, and early 2000s.)

Greater labor force participation is associated with higher tax revenues because the number of employed people, and therefore the number of people paying income and payroll taxes, tends to rise. It is also associated with lower spending on means-tested programs (which provide cash payments or other forms of assistance to people with relatively low income or few assets), such as Medicaid, and on refundable tax credits.

Changes in the labor force participation rate can distort the significance of the unemployment rate—that is, the share of people in the labor force without a job—as a measure of the health of the economy. For example, between the end of the 2007–2009 recession and 2017, the unemployment rate for people ages 25 to 54 fell by 4.5 percentage points even though the share of that population with a job increased by just 3 percentage points. The unemployment rate declined partly because of an increase in the share of the population that was employed but also because of a decrease in the labor force participation rate.

[334] Webpage: “Labor Force Participation.” Bureau of Labor Statistics. Last modified July 28, 2017. <www.bls.gov>

Basic concepts

• The labor force participation rate is the percentage of the population that is either employed or unemployed (that is, either working or actively seeking work)

• People with jobs are employed.

• People who are jobless, looking for a job, and available for work are unemployed.

• The labor force is made up of the employed and the unemployed.

• People who are neither employed nor unemployed are not in the labor force.

[335] Webpage: “Glossary.” Bureau of Labor Statistics. Last modified June 7, 2016. <www.bls.gov>

Civilian noninstitutional population (Current Population Survey)

Included are persons 16 years of age and older residing in the 50 states and the District of Columbia who do not live in institutions (for example, correctional facilities, long-term care hospitals, and nursing homes) and who are not on active duty in the Armed Forces.

[336] Chart constructed with data from:

a) Dataset: “LNU01324887. Labor Force Participation Rate, 16 to 24 Years, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

b) Dataset: “LNU01324885. Labor Force Participation Rate, 16 to 24 Years, Men, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

c) Dataset: “LNU01324886. Labor Force Participation Rate, 16 to 24 Years, Women, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

d) Dataset: “LNU01300089. Labor Force Participation Rate, 25 to 34 Years, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

e) Dataset: “LNU01300164. Labor Force Participation Rate, 25 to 34 Years, Men, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

f) Dataset: “LNU01300327. Labor Force Participation Rate, 25 to 34 Years, Women, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

g) Dataset: “LNU01300091. Labor Force Participation Rate, 35 to 44 Years, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

h) Dataset: “LNU01300173. Labor Force Participation Rate, 35 to 44 Years, Men, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

i) Dataset: “LNU01300334. Labor Force Participation Rate, 35 to 44 Years, Women, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

j) Dataset: “LNU01300093. Labor Force Participation Rate, 45 to 54 Years, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

k) Dataset: “LNU01300182. Labor Force Participation Rate, 45 to 54 Years, Men, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

l) Dataset: “LNU01300341. Labor Force Participation Rate, 45 to 54 Years, Women, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

m) Dataset: “LNU01300095. Labor Force Participation Rate, 55 to 64 Years, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

n) Dataset: “LNU01300190. Labor Force Participation Rate, 55 to 64 Years, Men, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

o) Dataset: “LNU01300347. Labor Force Participation Rate, 55 to 64 Years, Women, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

p) Dataset: “LNU01300097. Labor Force Participation Rate, 65 Years and Over, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

q) Dataset: “LNU01300199. Labor Force Participation Rate, 65 Years and Over, Men, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

r) Dataset: “LNU01300354. Labor Force Participation Rate, 65 Years and Over, Women, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

[337] Article: “Labor Force Projections to 2024: The Labor Force Is Growing, but Slowly.” By Mitra Toossi. U.S. Bureau of Labor Statistics Monthly Labor Review, December 2015. <www.bls.gov>

Page 2: “Prime-age workers—those between the ages of 25 and 54—are projected to have a growth rate of 0.4 percent and are expected to make up nearly 64 percent of the labor force in 2024.”

[338] Calculated with data from:

a) Dataset: “LNU01000061. Civilian Labor Force Level, 25 to 54 Years, Men, 1976–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 15, 2017 at <data.bls.gov>

b) Dataset: “LNU05000061. Not in Labor Force, 25 to 54 Years, Men, 1976–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 15, 2017 at <data.bls.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[339] Chart constructed with data from:

a) Dataset: “LNU01324885. Labor Force Participation Rate, 16 to 24 Years, Men, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

b) Dataset: “LNU01324886. Labor Force Participation Rate, 16 to 24 Years, Women, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

c) Dataset: “LNU01300061. Labor Force Participation Rate, 25 to 54 Years, Men, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

d) Dataset: “LNU01300062. Labor Force Participation Rate, 25 to 54 Years, Women, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

q) Dataset: “LNU01324231. Labor Force Participation Rate, 55 Years and Over, Men, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

r) Dataset: “LNU01324232. Labor Force Participation Rate, 55 Years and Over, Women, 1948–2017.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed June 8, 2017 at <data.bls.gov>

[340] Webpage: “Glossary.” Bureau of Labor Statistics. Last modified June 7, 2016. <www.bls.gov>

Employed persons (Current Population Survey)

Persons 16 years and over in the civilian noninstitutional population who, during the reference week, (a) did any work at all (at least 1 hour) as paid employees; worked in their own business, profession, or on their own farm, or worked 15 hours or more as unpaid workers in an enterprise operated by a member of the family; and (b) all those who were not working but who had jobs or businesses from which they were temporarily absent because of vacation, illness, bad weather, childcare problems, maternity or paternity leave, labor-management dispute, job training, or other family or personal reasons, whether or not they were paid for the time off or were seeking other jobs. Each employed person is counted only once, even if he or she holds more than one job. Excluded are persons whose only activity consisted of work around their own house (painting, repairing, or own home housework) or volunteer work for religious, charitable, and other organizations.

[341] Webpage: “Glossary.” Bureau of Labor Statistics. Last modified June 7, 2016. <www.bls.gov>

Unemployed persons (Current Population Survey)

Persons aged 16 years and older who had no employment during the reference week, were available for work, except for temporary illness, and had made specific efforts to find employment sometime during the 4-week period ending with the reference week. Persons who were waiting to be recalled to a job from which they had been laid off need not have been looking for work to be classified as unemployed.

[342] Webpage: “Glossary.” Bureau of Labor Statistics. Last modified June 7, 2016. <www.bls.gov>

“The unemployment rate represents the number unemployed as a percent of the labor force.”

[343] Webpage: “Labor Force Statistics from the Current Population Survey: Labor Force Characteristics.” Bureau of Labor Statistics. Last modified April 18, 2017. <www.bls.gov>

Not in the labor force

Persons who are neither employed nor unemployed are not in the labor force. This category includes retired persons, students, those taking care of children or other family members, and others who are neither working nor seeking work. Information is collected on their desire for and availability for work, job search activity in the prior year, and reasons for not currently searching.

[344] Webpage: “Glossary.” Bureau of Labor Statistics. Last modified June 7, 2016. <www.bls.gov>

Not in the labor force (Current Population Survey)

Includes persons aged 16 years and older in the civilian noninstitutional population who are neither employed nor unemployed in accordance with the definitions contained in this glossary. Information is collected on their desire for and availability for work, job search activity in the prior year, and reasons for not currently searching.

[345] Dataset: “LNU04000000. Annual Unemployment Rate, 16 Years and Over, 1947–2016.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed August 28, 2017 at <data.bls.gov>

[346] Webpage: “Alternative Measures of Labor Underutilization for States, Fourth Quarter of 2016 through Third Quarter of 2017 Averages.” U.S. Bureau of Labor Statistics. Last modified October 27, 2017. <www.bls.gov>

Six alternative measures of labor underutilization have long been available on a monthly basis from the Current Population Survey (CPS) for the United States as a whole. … The official concept of unemployment (as measured in the CPS by U-3 in the U-1 to U-6 range of alternatives) includes all jobless persons who are available to take a job and have actively sought work in the past four weeks. …

The six state measures are based on the same definitions as those published for the United States:

• U-1, persons unemployed 15 weeks or longer, as a percent of the civilian labor force;

• U-2, job losers and persons who completed temporary jobs, as a percent of the civilian labor force;

• U-3, total unemployed, as a percent of the civilian labor force (this is the definition used for the official unemployment rate);

• U-4, total unemployed plus discouraged workers, as a percent of the civilian labor force plus discouraged workers;

• U-5, total unemployed, plus discouraged workers, plus all other marginally attached workers, as a percent of the civilian labor force plus all marginally attached workers; and

• U-6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons, as a percent of the civilian labor force plus all marginally attached workers.

Definitions for the economic characteristics underlying the three broader measures of labor underutilization are worth mentioning here. Discouraged workers (U-4, U-5, and U-6 measures) are persons who are not in the labor force, want and are available for work, and had looked for a job sometime in the prior 12 months. They are not counted as unemployed because they had not searched for work in the prior 4 weeks, for the specific reason that they believed no jobs were available for them. The marginally attached (U-5 and U-6 measures) are a group that includes discouraged workers. The criteria for the marginally attached are the same as for discouraged workers, with the exception that any reason could have been cited for the lack of job search in the prior 4 weeks. Persons employed part time for economic reasons (U-6 measure) are those working less than 35 hours per week who want to work full time, are available to do so, and gave an economic reason (their hours had been cut back or they were unable to find a full-time job) for working part time. These individuals are sometimes referred to as involuntary part-time workers.

Generally, all six measures of labor underutilization move together over time, including across business cycles. Similarly, states that have low unemployment rates tend to have low values for the other five measures; the reverse is true for states with high unemployment rates.

[347] Book: Essentials of Economics (2nd edition). By Paul Krugman, Robin Wells, and Kathryn Graddy. Macmillan, 2010.

Page 334:

The Bureau of Labor Statistics is the federal agency that calculates the official unemployment rate. It also calculates broader “measures of labor underutilization” that include the three categories of frustrated workers. Figure 12-2 shows what happens to the measured unemployment rate once discouraged workers, marginally attached workers, and the underemployed are counted. The broadest measure of un- and underemployment, known as U6, is the sum of these three measures plus the unemployed; it is substantially higher than the rate usually quoted by the news media.

[348] Dataset: “LNS13327709. Total Unemployed, Plus All Marginally Attached Workers Plus Total Employed Part Time for Economic Reasons, as a Percent of All Civilian Labor Force Plus All Marginally Attached Workers, 1947–2016.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed December 8, 2017 at <data.bls.gov>

[349] “American Time Use Survey—2016 Results.” U.S. Bureau of Labor Statistics, June 27, 2017. <www.bls.gov>

Page 9: “Table 1. Time spent in primary activities and percent of the civilian population engaging in each activity, averages per day by sex, 2016 annual averages”

Page 4:

The estimates in this news release are based on annual average data from the American Time Use Survey (ATUS). The ATUS, which is conducted by the U.S. Census Bureau for the Bureau of Labor Statistics (BLS), is a continuous survey about how individuals age 15 and over spend their time. …

… In 2016, approximately 10,500 individuals were interviewed. …

ATUS sample households are chosen from the households that completed their eighth (final) interview for the Current Population Survey (CPS), the nation’s monthly household labor force survey. ATUS sample households are selected to ensure that estimates will be nationally representative.

One individual age 15 or over is randomly chosen from each sampled household. This “designated person” is interviewed by telephone once about his or her activities on the day before the interview—the “diary day.” …

ATUS designated persons are preassigned a day of the week about which to report. Preassignment is designed to reduce variability in response rates across the week and to allow oversampling of weekend days so that accurate weekend day measures can be developed. Interviews occur on the day following the assigned day. For example, a person assigned to report about a Monday would be contacted on the following Tuesday. Ten percent of designated persons are assigned to report about each of the five weekdays. Twenty-five percent are assigned to report about each weekend day. …

In the time diary portion of the ATUS interview, survey respondents sequentially report activities they did between 4 a.m. on the day before the interview until 4 a.m. on the day of the interview. For each activity, respondents are asked how long the activity lasted. For activities other than personal care activities (such as sleeping and grooming), interviewers also ask respondents where they were and who was in the room with them (if at home) or who accompanied them (if away from home). If respondents report doing more than one activity at a time, they are asked to identify which one was the “main” (primary) activity. If none can be identified, then the interviewer records the first activity mentioned. After completing the time diary, interviewers ask respondents additional questions to clearly identify work, volunteering, eldercare, and secondary childcare activities. Secondary childcare is defined as having a child under age 13 in one’s care while doing other activities. …

Average day. The average day measure reflects an average distribution across all persons in the reference population and all days of the week. The ATUS collects data about daily activities from all segments of the population age 15 and over, including persons who are employed and not employed.

Pages 6–7:

The following definitions describe the activity categories shown in this report. All major time-use categories in this release include related travel time and waiting time. For example, time spent “driving to the stadium” and time spent “waiting to get into the stadium to play ball” are included in Leisure and sports.

Personal care activities. Personal care activities include sleeping, grooming (such as bathing or dressing), health-related self-care, and personal or private activities. Receiving unpaid personal care from others (for example, “my sister put polish on my nails”) also is captured in this category. In general, respondents are not asked who they were with or where they were for personal care activities, as such information can be sensitive.

Eating and drinking. All time spent eating or drinking (except eating and drinking done as part of a work or volunteer activity), whether alone, with others, at home, at a place of purchase, or somewhere else, is classified here.

Household activities. Household activities are activities done by people to maintain their households. These include housework; cooking; lawn and garden care; pet care; vehicle maintenance and repair; home maintenance, repair, decoration, and renovation; and household management and organizational activities (such as filling out paperwork or planning a party). Food preparation, whether or not reported as done specifically for another household member, is always classified as a household activity unless it was done as a volunteer, work, or income-generating activity. For example, “making breakfast for my son” is coded as a household activity, not as childcare.

Purchasing goods and services. This category includes time spent purchasing consumer goods, professional and personal care services, household services, and government services. Consumer purchases include most purchases and rentals of consumer goods, regardless of the mode or place of purchase or rental (in person, via telephone, over the Internet, at home, or in a store). Gasoline, grocery, other food purchases, and all other shopping are further broken out in subcategories.

Time spent obtaining, receiving, and purchasing professional and personal care services provided by someone else also is classified in this category. Professional services include childcare, financial services and banking, legal services, medical and adult care services, real estate services, and veterinary services. Personal care services include day spas, hair salons and barbershops, nail salons, and tanning salons. Activities classified here include time spent paying, meeting with, or talking to service providers, as well as time spent receiving the service or waiting to receive the service.

Time spent arranging for and purchasing household services provided by someone else also is classified here. Household services include housecleaning; cooking; lawn care and landscaping; pet care; tailoring, laundering, and dry cleaning; vehicle maintenance and repairs; and home repairs, maintenance, and construction.

This category also captures the time spent obtaining government services—such as applying for food stamps— and purchasing government-required licenses or paying fines or fees.

Caring for and helping household members. Time spent doing activities to care for or help any child (under age 18) or adult in the household, regardless of relationship to the respondent or the physical or mental health status of the person being helped, is classified here. Caring for and helping activities for household children and adults are coded separately in subcategories.

Primary childcare activities include time spent providing physical care; playing with children; reading with children; assistance with homework; attending children’s events; taking care of children’s health needs; and dropping off, picking up, and waiting for children. Passive childcare done as a primary activity (such as “keeping an eye on my son while he swam in the pool”) also is included. A child’s presence during the activity is not enough in itself to classify the activity as childcare. For example, “watching television with my child” is coded as a leisure activity, not as childcare.

Secondary childcare occurs when persons have a child under age 13 “in their care” while doing activities other than primary childcare. For a complete definition, see the Concepts and definitions section of this Technical Note. Caring for and helping household members also includes a range of activities done to benefit adult members of households, such as providing physical and medical care or obtaining medical services. Doing something as a favor for or helping another household adult does not automatically result in classification as a helping activity.

For example, a report of “helping my spouse cook dinner” is considered a household activity (food preparation), not a helping activity, because cooking dinner benefits the household as a whole. By contrast, doing paperwork for another person usually benefits the individual, so a report of “filling out an insurance application for my spouse” is considered a helping activity.

Caring for and helping nonhousehold members. This category includes time spent in activities done to care for or help others—both children (under age 18) and adults—who do not live in the household. When done for or through an organization, time spent helping nonhousehold members is classified as volunteering, rather than as helping nonhousehold members. Care of nonhousehold children, even when done as a favor or helping activity for another adult, is always classified as caring for and helping nonhousehold children, not as helping another adult.

Working and work-related activities. This category includes time spent working, doing activities as part of one’s job, engaging in income-generating activities not as part of one’s job, and job search activities. “Working” includes hours spent doing the specific tasks required of one’s main or other job, regardless of location or time of day. “Work-related activities” include activities that are not obviously work but are done as part of one’s job, such as having a business lunch and playing golf with clients.

“Other income-generating activities” are those done “on the side” or under informal arrangement and are not part of a regular job. Such activities might include selling homemade crafts, maintaining a rental property, or having a yard sale. These activities are those for which people are paid or will be paid.

Travel time related to working and work-related activities includes time spent traveling to and from work, as well as time spent traveling for work-related, income-generating, and job search activities.

Educational activities. Time spent taking classes for a degree or for personal interest (including taking Internet or other distance-learning courses), time spent doing research and homework, and time spent taking care of administrative tasks related to education (such as registering for classes or obtaining a school ID) are included in this category. For high school students, before- and after-school extracurricular activities (except sports) also are classified as educational activities. Educational activities do not include time spent for classes or training received as part of a job. Time spent helping others with their education-related activities is classified as an activity involving caring for and helping others.

Organizational, civic, and religious activities. This category captures time spent volunteering for or through an organization, performing civic obligations, and participating in religious and spiritual activities. Civic obligations include government-required duties, such as serving jury duty or appearing in court, and activities that assist or influence government processes, such as voting or attending town hall meetings. Religious activities include those normally associated with membership in or identification with specific religions or denominations, such as attending religious services; participating in choirs, youth groups, orchestras, or unpaid teaching (unless identified as volunteer activities); and engaging in personal religious practices, such as praying.

Leisure and sports. The leisure and sports category includes time spent in sports, exercise, and recreation; socializing and communicating; and other leisure activities. Sports, exercise, and recreation activities include participating in—as well as attending or watching—sports, exercise, and recreational activities. Recreational activities include yard games like croquet or horseshoes, as well as activities like billiards and dancing. Socializing and communicating includes face-to-face social communication and hosting or attending social functions. Leisure activities include watching television; reading; relaxing or thinking; playing computer, board, or card games; using a computer or the Internet for personal interest; playing or listening to music; and other activities, such as attending arts, cultural, and entertainment events.

Telephone calls, mail, and e-mail. This category captures time spent in telephone communication and household or personal mail or e-mail. This category also includes texting and Internet voice and video calling. Telephone and Internet purchases are classified in Purchasing goods and services. Telephone calls, mail, or email identified as related to work or volunteering are classified as work or volunteering.

Other activities, not elsewhere classified. This residual category includes security procedures related to traveling, traveling not associated with a specific activity category, ambiguous activities that could not be coded, and missing activities. Missing activities result when respondents did not remember what they did for a period of time, or when they considered an activity too private or personal to report.

[350] “American Time Use Survey—2016 Results.” U.S. Bureau of Labor Statistics, June 27, 2017. <www.bls.gov>

Pages 11–12: “Table 3. Time spent in primary activities for the civilian population by age, sex, race, Hispanic or Latino ethnicity, marital status, and educational attainment, 2016 annual averages”

NOTE: See footnote above for detailed descriptions of all activities.

[351] Report: Historical Statistics of the United StatesColonial Times to 1970, Part 1. U.S. Department of Commerce, 1975. <fraser.stlouisfed.org>

Page 151: “765-778. Average hours and average earnings in manufacturing, in selected nonmanufacturing industries, and for ‘lower-skilled’ labor, 1890–1926. Source: Paul H. Douglas, Real Wages in the United States, 1890–1926, Houghton Mifflin Company, New York, 1930 (copyright).”

Page 168: “Series D 765-778. Average Hours and Average Earnings In Manufacturing, In Selected Nonmanufacturing Industries, and for ‘Lower-Skilled’ Labor 1890 to 1926. Manufacturing Industries … Total … Weekly hours … 765 [series] Year [=] 1890 [=] 60.0”

[352] Calculated with the dataset: “CES3000000002. Employment, Hours, and Earnings, Current Employment Statistics Survey, Manufacturing, 2007–2017.” Bureau of Labor Statistics. Accessed August 18, 2017 at <data.bls.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[353] Calculated with data from:

a) Dataset: “Table 6.9B. Hours Worked by Full-Time and Part-Time Employees by Industry.” U.S. Department of the Treasury, Bureau of Economic Analysis. August 06, 2015. <bea.gov>

b) Dataset: “Table 6.9D. Hours Worked by Full-Time and Part-Time Employees by Industry.” U.S. Department of the Treasury, Bureau of Economic Analysis. August 03, 2015. <bea.gov>

c) Dataset: “Table 6.4B. Full-Time and Part-Time Employees by Industry.” U.S. Department of the Treasury, Bureau of Economic Analysis. August 06, 2015. <bea.gov>

d) Dataset: “Table 6.4D. Full-Time and Part-Time Employees by Industry.” U.S. Department of the Treasury, Bureau of Economic Analysis. August 03, 2015. <bea.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[354] Calculated with data from:

a) Dataset: “Table 6.9B. Hours Worked by Full-Time and Part-Time Employees by Industry.” U.S. Department of the Treasury, Bureau of Economic Analysis. August 06, 2015. <bea.gov>

b) Dataset: “Table 6.9C. Hours Worked by Full-Time and Part-Time Employees by Industry.” U.S. Department of the Treasury, Bureau of Economic Analysis. August 06, 2015. <bea.gov>

c) Dataset: “Table 6.9D. Hours Worked by Full-Time and Part-Time Employees by Industry.” U.S. Department of the Treasury, Bureau of Economic Analysis. August 03, 2015. <bea.gov>

d) Dataset: “Table 6.4B. Full-Time and Part-Time Employees by Industry.” U.S. Department of the Treasury, Bureau of Economic Analysis. August 06, 2015. <bea.gov>

e) Dataset: “Table 6.4C. Full-Time and Part-Time Employees by Industry.” U.S. Department of the Treasury, Bureau of Economic Analysis. August 06, 2015. <bea.gov>

f) Dataset: “Table 6.4D. Full-Time and Part-Time Employees by Industry.” U.S. Department of the Treasury, Bureau of Economic Analysis. August 03, 2015. <bea.gov>

g) Dataset: “Table 7.1. Selected Per Capita Product and Income Series in Current and Chained Dollars.” U.S. Department of Commerce, Bureau of Economic Analysis. Last revised April 28, 2016. <www.bea.gov>

NOTE: An Excel file containing the data and calculations is available upon request.

[355] Report: “American Time Use Survey—2015 Results.” U.S. Department of Labor, Bureau of Labor Statistics, June 24, 2016. <www.bls.gov>

Page 1:

Working (by Employed Persons) in 2015

Employed persons worked an average of 7.6 hours on the days they worked. More hours were worked, on average, on weekdays than on weekend days—8.0 hours compared with 5.6 hours.

Page 4:

The estimates in this news release are based on annual average data from the American Time Use Survey (ATUS). The ATUS, which is conducted by the U.S. Census Bureau for the Bureau of Labor Statistics (BLS), is a continuous survey about how individuals age 15 and over spend their time.

Survey methodology

Data collection for the ATUS began in January 2003. Sample cases for the survey are selected monthly, and interviews are conducted continuously throughout the year. In 2015, approximately 10,900 individuals were interviewed. Estimates are released annually.

ATUS sample households are chosen from the households that completed their eighth (final) interview for the Current Population Survey (CPS), the nation’s monthly household labor force survey. ATUS sample households are selected to ensure that estimates will be nationally representative. One individual age 15 or over is randomly chosen from each sampled household

Concepts and definitions

Average day. The average day measure reflects an average distribution across all persons in the reference population and all days of the week.

Page 6:

Weekday, weekend, and holiday estimates. Estimates for weekdays are an average of reports about Monday through Friday. Estimates for weekend days and holidays are an average of reports about Saturdays, Sundays, and the following holidays: New Year’s Day, Easter, Memorial Day, the Fourth of July, Labor Day, Thanksgiving Day, and Christmas Day. Data were not collected about New Year’s Day in 2012, and Christmas Day in 2011 and 2014.

Page 13:

Table 4. Employed persons working and time spent working on days worked by full- and part-time status and sex, jobholding status, educational attainment, and day of week, 2015 annual averages … Characteristic [=] Full-time workers … Employed persons who worked on an average day … Average hours of work [=] 7.60, Employed persons who worked on an average weekday … Average hours of work [=] 7.95, Employed persons who worked on an average Saturday, Sunday, and holiday … Average hours of work [=] 5.57.

[356] Webpage: “American Time Use Survey Technical Note.” U.S. Department of Labor, Bureau of Labor Statistics. Last modified on June 27, 2017. <www.bls.gov>

About the questionnaire

In the time diary portion of the ATUS interview, survey respondents sequentially report activities they did between 4 a.m. on the day before the interview until 4 a.m. on the day of the interview. For each activity, respondents are asked how long the activity lasted. For activities other than personal care activities (such as sleeping and grooming), interviewers also ask respondents where they were and who was in the room with them (if at home) or who accompanied them (if away from home). If respondents report doing more than one activity at a time, they are asked to identify which one was the “main” (primary) activity. If none can be identified, then the interviewer records the first activity mentioned. After completing the time diary, interviewers ask respondents additional questions to clearly identify work, volunteering, eldercare, and secondary childcare activities. Secondary childcare is defined as having a child under age 13 in one’s care while doing other activities.

[357] Webpage: “About the Monthly Labor Review.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed December 22, 2016 at <www.bls.gov>

About the Monthly Labor Review

Established in 1915, Monthly Labor Review (MLR) is the principal journal of fact, analysis, and research from the U.S. Bureau of Labor Statistics, an agency within the U.S. Department of Labor. Each month, economists, statisticians, and experts from the Bureau join with private sector professionals and state and local government specialists to provide a wealth of research in a wide variety of fields—the labor force, the economy, employment, inflation, productivity, occupational injuries and illnesses, wages, prices, and more.

[358] Article: “The Overestimated Workweek Revisited.” By John P. Robinson, Steven Martin, Ignace Glorieux, and Joeri Minnen. U.S. Bureau of Labor Statistics Monthly Labor Review, June 2011. <www.bls.gov>

Page 48:

It can be seen that, for both the questions about usual work hours and the question about work hours from the previous week, and for both female and male workers, the estimates are larger than the diary figures, as hypothesized and as found in previous studies. That gap tends to be larger for full-time workers than for full-time and part-time workers together, and larger for women than men. The gap between the answers to the CPS question on actual hours and the diary data is lower than both of the other gaps for men and women together, but not lower than both for men and women separately. The “estimate–diary” gaps range from 2.1 hours to 6.3 hours; in other words, relative to the work hours they recorded in their diaries, when asked how many hours they usually worked or had worked the previous week, people overestimated by between 5 percent and 12 percent.

Pages 50–51:

As noted earlier, there may still be ambiguities in survey questions that underlie gaps between people’s responses to estimate questions and the hours they report in time diaries. The possibility that respondents might include their time spent commuting or on their lunch breaks in their estimates of work hours was minimized in the Belgian survey, but the possibility still exists. Moreover, it is also possible that workers fail to subtract time lost to household crises or other sudden nonwork demands (such as the need to take care of a sick child or repair one’s car). …

This article has compared data from time diaries on the number of hours people worked with data gathered from employed respondents who were asked to estimate directly the number of hours they usually work or actually worked. Results suggest that, overall, the “estimate questions” generate higher estimates of the time men and women spend doing paid work than do figures from daily diaries that are extrapolated across the week. Moreover, there is consistent evidence that larger discrepancies tend to arise from respondents who estimate more hours in their workweek.

[359] A Textbook of Human Resource Management. By R.S. Dwivedi. Vikas Publishing House, 2009.

Page 233: “There are several considerations or criteria which help in determining wages in an enterprise. The criteria include: (a) law of supply and demand, (b) prevailing wages, (c) ability to pay, (d) governmental factors, (e) standard and cost of living, (f) productivity, (g) bargaining power, and (h) job requirements.”

[360] Book: The Oxford Handbook of Economic Geography. By Gordon L. Clark, Meric S. Gertler, Maryann P. Feldman, and Kate Williams. OUP Oxford, 2003.

Page 482: “The exogenous characteristics of a region may also affect the productivity of labor. In regions with endowments that raise labor productivity, firms will be willing to pay workers high wages relative to other locations.”

[361] Book: Labor Economics (2nd edition). By Pierre Cahuc, Stephane Carcillo, and Andre Zylberberg. MIT Press, 2014.

Page xxiii: “This book is composed of four parts. Part One presents labor supply and demand behaviors. It shows how the interaction of supply and demand on competitive markets determines wages and employment. It also shows how the mechanisms of competition drive investments in education and training.”

[362] Book: Cross-border Human Resources, Labor, and Employment Issues: Proceedings of the New York University 54th Annual Conference on Labor. By Andrew P. Morriss and Samuel Estreicher. Kluwer Law International, 2005.

Pages 417–418:

Any mandated benefit can have this effect on employees who earn the minimum wage. If their compensation package does not include any voluntarily provided benefits (fringe benefits), then upon enactment of a new mandated benefit, the employer cannot reduce their wage rate due to the minimum wage laws.85 But all this is true only in the short term. In the long run, these employees will pay for the benefit by not receiving wage raises that they otherwise would have received, since the employer would strive to return to her pre-mandated-benefit output.

85 See Gruber and Krueger, supra note 23, at 139 (noting that mandated health insurance may have greater adverse effects on employment level, i.e., less shifting of costs through lower wages, because the minimum wage is likely to be more of a constraint for uninsured workers).

Page 445:

The second labor standard regulation in Table 2 is the Davis–Bacon Act. Dating to 1931, Davis–Bacon requires government contractors to pay the local prevailing wages to labor in public works projects. ‘Prevailing wages’ are set by the Department of Labor’s Wage and Hour Division and are generally significantly higher than market wages.16 Because of this, Davis–Bacon imposes costs on contractors in the form of higher wages than they would pay on a non-government contract job. The costs of the Davis–Bacon Act as measured by a number of studies are the transfers to labor from taxpayers in the form of higher wages paid on government contracts.

16 Rather than allowing the market to simply determine a wage, WHD sets ‘prevailing wages’ that must be paid by employers contracting with the government. The prevailing wage tables are issued by WHD and are not based on market wages, but rather on various features of location and conditions in the market. While the factors used to establish prevailing wages would likely affect market wages, the adjustments made by WHD are arbitrary.

[363] Book: Industrial and Labor Economics: Issues in Developing and Transition Countries. By Saibal Kar and Debabrata Datta. Springer, 2014.

Page 91:

One of the earliest attempts criticizing the traditional analyses was made by Slichter (1950). He argued that the empirical evidence of the variation in earnings of homogeneous employers could not be explained by the competitive model. The paper, based on data from the US manufacturing sector, showed a positive correlation between wages and employers’ ability to pay. Lester (1952) also echoed similar sentiments. In Lester’s terminology, there exists a feasible range of wage rates, and a central task of labor economics is to uncover the determinants of its size. However, this effort did not find any progress immediately as the issue was not pursued further2 till the decade of the 1980’s. In the late 1980’s, a resurgence of the issue took place owing to the worldwide concern about high and persistent unemployment rates.

2 With few exceptions, Hicks (1963) and Mackay (1972) talked about profits’ relevance and questioned the validity of the competitive model.

[364] Book: Government Regulation of the Employment Relationship. By Bruce E. Kaufman. Cornell University Press, 1997.

Pages 179–180:

For the first seventy years of this century, labor market policies increasingly limited and directed competition through public regulation of wages, hours, and conditions of work. The policies of the last twenty years have been far more mixed. Certain types of regulation, notably those intended to ameliorate the social consequences of markets, have been extended. Legislation, such as the Americans with Disabilities act, the Civil Rights Act of 1991, and the Family Medical Leave Act, has increased employee rights, extended government’s role in labor markets, and further enmeshed market processes within an institutional framework. In contrast, government direction of the economic functions of labor markets has been sharply curtailed as price mechanisms have won increasing acceptance as the primary regulator. Since the 1970s federal and state policy makers have loosened, repealed, and reinterpreted laws directly governing the employment relation, such as area wage standards, work at home, minimum wages, eligibility requirements for unemployment insurance, disability standards under workers’ compensation, and employer tactics in labor relations. Inaction in adapting regulation to changes in the employment relationship—changes such as widespread use of subcontractors and temporary workers in place of conventional employees—has likewise exposed an increasing potion of the labor force to the forces of the unconstrained market. The role of the price mechanisms in labor markets has also been magnified by the economic deregulation of core transportation industries—airlines, trucking, and railroads, along with telecommunication and banking. Movement toward more openness in trade has had parallel effects in manufacturing. Such policies have placed wages and conditions of work in competition to an extent not seen for nearly a century. Current state and federal legislation portends continuing movement toward market regulation in the near term.

[365] Book: Principles of Management (3rd edition). By P N P and Reddy Tripathi. Tata McGraw–Hill Education, 2005.

Page 219: “The cost of living of workers also has a strong influence on the rate of wages. If this factor is not considered, the labourers may not be in a position to make both ends meet and this will affect their efficiency. Hence progressive employers consider this factor also.”

[366] Book: Macroeconomics: Australasian Edition (4th edition). By Olivier Blanchard and Jeffrey Sheen. Pearson Higher Education AU, 2013.

Page 142:

Bargaining power and wage determination.

Even in the absence of collective bargaining, workers do have some bargaining power that allows them to receive wages higher than their reservation wage. Each worker’s bargaining power depends both on the nature of their job and on the economy-wide labour markets conditions. Let’s consider each factor in turn.

[367] Book: Managing Compensation (and Understanding it Too): A Handbook for the Perplexed. By Donald L. Caruth and Gail D. Handlogten. Greenwood Publishing Group, 2001.

Page 10:

Another determinant of compensation rates is the requirements of performing a particular job. Where long training periods are required to learn the skills necessary for successful job performance, compensation rates tend to be higher than they are for jobs where the training period is short or nonexistent. Higher rates attract more people to the field, thereby assuring employers of an adequate pool of talent from which to select employees.

[368] News release: “Employer Costs for Employee Compensation—December 2016.” U.S. Department of Labor, Bureau of Labor Statistics, September 8, 2016. <www.bls.gov>

Page 1: “Employer costs for employee compensation averaged $34.90 per hour worked in December 2016, the U.S. Bureau of Labor Statistics reported today. Wages and salaries averaged $23.87 per hour worked and accounted for 68.4 percent of these costs, while benefits averaged $11.03 and accounted for the remaining 31.6 percent.”

Page 3:

Employer Costs for Employee Compensation (ECEC) measures the average cost to employers for wages and salaries and benefits per employee hour worked.

ECEC includes the civilian economy, which includes data from both private industry and state and local government. Excluded from private industry are the self-employed and farm and private household workers. Federal government workers are excluded from the public sector. The private industry series and the state and local government series provide data for the two sectors separately.

Sample size

Data for the December 2016 reference period were collected from a probability sample of approximately 28,100 occupational observations selected from a sample of about 6,800 private industry establishments and approximately 8,000 occupational observations selected from a sample of about 1,400 state and local government establishments that provided data at the initial interview. This quarter, the state and local government sample was replaced in its entirety. It was last replaced in December 2007. The government sample is replaced less frequently than the private industry sample. One-third of the private sample is rotated each year except in years when the government sample is replaced.

[369] Article: “Employer Costs for Employee Compensation: Tracking Changes in Benefit Costs.” By William J. Wiatrowski. U.S. Bureau of Labor Statistics Compensation and Working Conditions, Spring 1999. <www.bls.gov>

Page 32:

In the final four decades of the 20th century, employee compensation, as measured by employer costs, has undergone dramatic shifts. In 1959, cash payments (including straight-time pay, premium pay, bonuses, and paid leave) comprised 91 percent of all compensation costs for production workers in manufacturing industries; this fell to 78 percent by 1998. The remaining employer compensation costs were for benefits—those non-wage items that generally provide time off, insurance protection, and retirement security. In 1959, the largest proportion of benefit expenditures was for paid time off; by 1998, the largest benefit expenditure was for legally required items, such as Social Security and Medicare.

These facts set the stage for the story of changes in compensation that have been widely reported and widely attributed to a variety of causes: New legally-required benefits such as Medicare, which didn’t exist in 1959; new and revised laws encouraging and regulating certain benefits, particularly retirement plans; changes in workforce demographics—notably more working women and younger retirees—leading to changes in compensation; and rising health care costs spurred by technological advances and increased demand. In contrast, the data also suggest that the primary compensation medium is still cash. 1 In contrast, the data also suggest that the primary compensation medium is still cash. This article traces data from the Bureau of Labor Statistics on compensation costs over the past 40 years, exploring both the changes that have occurred and the similarities that still exist after two generations.

1 For a discussion of changes in compensation, see William J. Wiatrowski, “Family-related Benefits in the Workplace,” U.S. Bureau of Labor Statistics Monthly Labor Review, March 1990, pp. 28–33. Information on changes in labor force demographics may be found in Howard V. Hayghe, “Developments in Women’s Labor Force Participation,” U.S. Bureau of Labor Statistics Monthly Labor Review, September 1997, pp. 41–46, and in Diane Herz, “Work After Early Retirement: An Increasing Trend Among Men,” U.S. Bureau of Labor Statistics Monthly Labor Review, April 1995, pp. 13–20. Data on trends in health care costs are available in Report on the American Workforce, chapter 3 (U.S. Department of Labor, 1995).

[370] Report: “Reducing the Deficit: Spending and Revenue Options.” Congressional Budget Office, March 2011. <www.cbo.gov>

Page 133: “In the judgment of CBO and most economists, the employers’ share of payroll taxes is passed on to employees in the form of lower wages.”

[371] Report: “The Distribution of Household Income and Federal Taxes, 2008 and 2009.” Congressional Budget Office, July 10, 2012. <www.cbo.gov>

Page 23: “CBO further assumed—as do most economists—that employers pass on their share of payroll taxes to employees by paying lower wages than they would otherwise pay. Therefore, CBO included the employer’s share of payroll taxes in households’ before-tax income and in households’ taxes.”

[372] Report: “Understanding the Tax Reform Debate: Background, Criteria, & Questions.” Prepared under the direction of James R. White (Director, Strategic Issues, Tax Policy and Administration Issues). United States Government Accountability Office, September 2005. <www.gao.gov>

Page 68: “Payroll Taxes Often synonymous with social insurance taxes. However, in some cases the term ‘payroll taxes’ may be used more generally to include all tax withholding. For the purposes of this report, payroll taxes are synonymous with social insurance taxes.”

Page 69: “Social Insurance Taxes Tax payments to the federal government for Social Security, Medicare, and unemployment compensation. While employees and employers pay equal amounts in social insurance taxes, economists generally agree that employees bear the entire burden of social insurance taxes in the form of reduced wages.”

[373] Webpage: “Current-Law Distribution of Taxes.” Tax Policy Center (a joint project of the Urban Institute and Brookings Institution). Accessed March 11, 2017 at <www.taxpolicycenter.org>

“A key insight from economics is that taxes are not always borne by the individual or business that writes the check to the IRS. Sometimes taxes are shifted. For example, most economists believe that the employer portion of payroll taxes translate into lower wages and are thus ultimately borne by workers.”

[374] Report: “The Cost of the Affordable Care Act to Large Employers.” By Tevi D. Troy and D. Mark Wilson. American Health Policy Institute, 2014. <www.americanhealthpolicy.org>

Page i: “American Health Policy Institute (AHPI) is a new non-partisan 501(c)(3) think tank, established to examine the impact of health policy on large employers, and to explore and propose policies that will help bolster the ability of large employers to provide quality, affordable health care to employees and their dependents.”

Page 1: “The cost of the ACA to large U.S. employers (10,000 or more employees) is estimated to be between $4,800 to $5,900 per employee.”

Pages 10–11:

Appendix Two: Methodology

In January and February 2014 the American Health Policy Institute confidentially surveyed over 350 companies that are members of the HR Policy Association in order to identify and quantify the direct costs of the Affordable Care Act (ACA) for large employers. A small pilot survey conducted in December found that many, if not most, of the companies had already conducted analyses to quantify these costs, and that many of the analyses were conducted by outside consultants using very similar methodologies. In January, over 350 of the companies were asked to provide the following estimates for 2013 to 2023:

• Total U.S. employment of the company;

• Total number of lives covered by the companies health plans;

• Total baseline health care costs without enactment of the ACA; and

• Total estimated health care costs with the ACA.

[375] “2010 Annual Report of the Board of Trustees of The Federal Old-Age and Survivors Insurance and Disability Insurance Trust Funds.” Board of Trustees of the Federal OASDI Trust Funds, August 9, 2010. <www.ssa.gov>

Page 33:

[U]nder these new laws, a combination of federal subsidies for individual insurance through the health benefit exchanges, penalties for being uninsured or not offering coverage, an excise tax on employer sponsored group health insurance cost, and anticipated competitive premiums from health benefit exchanges are expected to slow the rate of growth in the total cost of employer-sponsored group health insurance. Most of this cost reduction is assumed to result in an increase in the share of employee compensation that will be provided in wages that will be subject to the Social Security payroll tax.

NOTE: To summarize the above, because the cost of health insurance is part of employers’ cost of compensating employees, if the cost of health insurance is decreased, “most” of the cost savings will be redirected to other forms of employee compensation such as salary. This is because employee compensation is generally driven by laws of supply of demand (with the notable exception of minimum wage laws). Likewise, because employer payroll taxes are a direct outcome of employers paying employees, most of this cost is redirected from other forms of employee compensation.

[376] Calculated with data from:

a) Dataset: “Employer Costs for Employee Compensation, Historical Listing, March 2004–December 2016.” U.S. Department of Labor, Bureau of Labor Statistics, 2017. <www.bls.gov>

Page 87: “Table 5. State and local government workers, by major occupational group: employer costs per hours worked for employee compensation and costs as a percentage of total compensation, 2004–2016”

Page 142: “Table 9. Private industry workers, by major occupational group: employer costs per hours worked for employee compensation and costs as a percentage of total compensation, 2004–2016”

b) Dataset: “Employer Costs for Employee Compensation, Historical Listing (Annual), 1986–2001.” U.S. Department of Labor, Bureau of Labor Statistics, June 19, 2002. <www.bls.gov>

Page 1:

The following tables provide data on Employer Costs for Employee Compensation (ECEC), a Bureau of Labor Statistics (BLS) compensation measure. The ECEC measures the average hourly cost that employers pay for wages and salaries plus the cost per hour worked for benefits. Computed from data collected for the Employment Cost Index (ECI), a principal Federal economic indicator published by BLS, the ECEC provides a snapshot of the structure of compensation at a specific point in time. The ECI, in contrast, is a fixed employment-weighted index that tracks changes in labor costs, free from the influence of employment shifts among occupations and industries. …

The ECEC is calculated by applying current, rather than fixed, employment weights to salary and benefit cost data from the establishments in the ECI survey. Estimates were published annually from 1986 through 2001 using payroll data that include March 12th as the reference period. Beginning in March 2002, data are available quarterly. ECEC data were first published for March 1986 and were limited to private industry. In 1988, the ECEC expanded to include data by bargaining status, more detailed major industry groups, and geographic regions. In 1991, ECEC data were published for civilian workers, State and local government workers, and private industry workers by establishment employment size.

Page 8: “Table 2. State and local government workers, by broad occupational group and for service industries: employer costs per hour worked for employee compensation and costs as a percent of total compensation, 1991–2001”

Page 12: “Table 3. Private industry workers, by occupational and industry group: employer costs per hour worked for employee compensation and costs as a percent of total compensation, 1986–2001”

c) Dataset: “Table 2.3.4. Price Indexes for Personal Consumption Expenditures by Major Type of Product, Seasonally Adjusted.” U.S. Department of Commerce, Bureau of Economic Analysis. Last revised June 28, 2016. <www.bea.gov>

Line 1: “Personal consumption expenditures (PCE)”

d) Dataset: “CPI Detailed Report Data for December 2015.” U.S. Department of Labor, Bureau of Labor Statistics, January 27, 2016.

“Table 24. Historical Consumer Price Index for All Urban Consumers (CPI-U): U. S. city average, all items (1982–84=100, unless otherwise noted)”

NOTES:

  • The 2004 employers’ costs were adjusted for inflation to 2015 dollars using the Personal Consumption Expenditure deflator.
  • An Excel file containing the data and calculations is available upon request.

[377] News release: “Employer Costs for Employee Compensation—December 2016.” U.S. Department of Labor, Bureau of Labor Statistics, March 17, 2017. <www.bls.gov>

Page 3:

Table A. Relative importance of employer costs for employee compensation, June 2016 … Private industry …. Compensation component … Wages and salaries [=] 69.7% … Benefits [=] 30.3 … Legally required … [=7.8] … State and local government … Wages and salaries [=] 63.0% … Benefits [=] 37.0 … Legally required [=] 5.6

Page 4:

Data for the December 2016 reference period were collected from a probability sample of approximately 28,100 occupational observations selected from a sample of about 6,800 private industry establishments and approximately 8,000 occupational observations selected from a sample of about 1,400 state and local government establishments that provided data at the initial interview. This quarter, the state and local government sample was replaced in its entirety. It was last replaced in December 2007. The government sample is replaced less frequently than the private industry sample. One-third of the private sample is rotated each year except in years when the government sample is replaced.

[378] Webpage: “Overtime Pay.” U.S. Department of Labor, Wage and Hour Division. Accessed April 21, 2017 at <www.dol.gov>

Overview

The federal overtime provisions are contained in the Fair Labor Standards Act (FLSA). Unless exempt, employees covered by the Act must receive overtime pay for hours worked over 40 in a workweek at a rate not less than time and one-half their regular rates of pay. There is no limit in the Act on the number of hours employees aged 16 and older may work in any workweek. The Act does not require overtime pay for work on Saturdays, Sundays, holidays, or regular days of rest, unless overtime is worked on such days.

The Act applies on a workweek basis. An employee’s workweek is a fixed and regularly recurring period of 168 hours—seven consecutive 24-hour periods. It need not coincide with the calendar week, but may begin on any day and at any hour of the day. Different workweeks may be established for different employees or groups of employees. Averaging of hours over two or more weeks is not permitted. Normally, overtime pay earned in a particular workweek must be paid on the regular pay day for the pay period in which the wages were earned.

[379] Webpage: “Handy Reference Guide to the Fair Labor Standards Act.” U.S. Department of Labor, Wage and Hour Division. Accessed April 21, 2017 at <www.dol.gov>

Exemptions

Some employees are exempt from the overtime pay provisions or both the minimum wage and overtime pay provisions.

Because exemptions are generally narrowly defined under the FLSA, an employer should carefully check the exact terms and conditions for each. Detailed information is available from local WHD offices.

Following are examples of exemptions which are illustrative, but not all-inclusive. These examples do not define the conditions for each exemption.

Exemptions from Both Minimum Wage and Overtime Pay

1. Executive, administrative, and professional employees (including teachers and academic administrative personnel in elementary and secondary schools), outside sales employees, and employees in certain computer-related occupations (as defined in DOL regulations);

2. Employees of certain seasonal amusement or recreational establishments, employees of certain small newspapers, seamen employed on foreign vessels, employees engaged in fishing operations, and employees engaged in newspaper delivery;

3. Farmworkers employed by anyone who used no more than 500 “man-days” of farm labor in any calendar quarter of the preceding calendar year;

4. Casual babysitters and persons employed as companions to the elderly or infirm.

Exemptions from Overtime Pay Only

1. Certain commissioned employees of retail or service establishments; auto, truck, trailer, farm implement, boat, or aircraft sales-workers; or parts-clerks and mechanics servicing autos, trucks, or farm implements, who are employed by non-manufacturing establishments primarily engaged in selling these items to ultimate purchasers;

2. Employees of railroads and air carriers, taxi drivers, certain employees of motor carriers, seamen on American vessels, and local delivery employees paid on approved trip rate plans;

3. Announcers, news editors, and chief engineers of certain non-metropolitan broadcasting stations;

4. Domestic service workers living in the employer’s residence;

5. Employees of motion picture theaters; and

6. Farmworkers.

Partial Exemptions from Overtime Pay

1. Partial overtime pay exemptions apply to employees engaged in certain operations on agricultural commodities and to employees of certain bulk petroleum distributors.

2. Hospitals and residential care establishments may adopt, by agreement with their employees, a 14-day work period instead of the usual 7-day workweek if the employees are paid at least time and one-half their regular rates for hours worked over 8 in a day or 80 in a 14-day work period, whichever is the greater number of overtime hours.

3. Employees who lack a high school diploma, or who have not attained the educational level of the 8th grade, can be required to spend up to 10 hours in a workweek engaged in remedial reading or training in other basic skills without receiving time and one-half overtime pay for these hours. However, the employees must receive their normal wages for hours spent in such training and the training must not be job specific.

4. Public agency fire departments and police departments may establish a work period ranging from 7 to 28 days in which overtime need only be paid after a specified number of hours in each work period.

[380] Article: “IBM Pays Tech Workers $65 Million To Settle Overtime Lawsuit.” Associated Press, November 26, 2006. <redmondmag.com>

International Business Machines Corp. settled a federal class-action lawsuit Wednesday, agreeing to pay a total of $65 million to 32,000 technology workers who claimed the company illegally withheld overtime pay.

The suit was filed in January in U.S. District Court in San Francisco on behalf of three employees who said they were forced to work more than 40 hours per week and on weekends without additional compensation.

The case involved workers classified as “Technical Services Professional and Information Technology Specialists.” IBM considered them highly skilled professionals exempt from overtime laws detailed in the Fair Labor Standards Act and California labor laws. …

… But the IBM workers were by no means the decision makers or creative types typically ineligible for overtime, said James M. Finberg, who represented the class for Lieff Cabraser Heimann & Bernstein LLP.

[381] Article: “I.B.M. Agrees to Pay $65 Million to Settle Dispute on Overtime.” By Bloomberg News. New York Times, November 23, 2006. <www.nytimes.com>

I.B.M. agreed yesterday to pay $65 million to settle accusations that it illegally denied overtime compensation to thousands of workers.

Under the settlement, some employees will be entitled to overtime payments based on a formula, the company, with headquarters in Armonk, N.Y., said. The employees contended that they had been wrongly classified as exempt from overtime pay.

The agreement, in the class-action suit filed on behalf of 32,000 workers, is subject to approval by Judge Phyllis J. Hamilton in United States District Court in San Francisco, where the case was filed.

[382] Article: “More American Workers Sue Employers for Overtime Pay.” By Paul Davidson. USA Today. Last updated April 19, 2012. <usatoday30.usatoday.com>

Companies say the lawsuits have forced them to grant workers less flexibility. Several years ago, IBM voluntarily reclassified 7,000 salaried technical and support workers earning an average $77,000 a year to hourly employees after it settled a class-action labor suit for $65 million. The company cut their base salaries 15% to account for potential overtime, says IBM’s MacDonald.

IBM’s Shar Anderson oversaw 20 workers in a customer service group. “It made me feel less valuable to the company,” says Anderson, 55, who has a bachelor’s degree in computer science and several professional certifications. Anderson, who’s now in a similar but higher-level salaried position, says she “wasn’t able to do my job” because she sometimes had to hand off emergency responses to colleagues after 5 p.m.

[383] Webpage: “The Executive Branch.” White House. Accessed December 9, 2017 at <www.whitehouse.gov>

Under Article II of the Constitution, the President is responsible for the execution and enforcement of the laws created by Congress. Fifteen executive departments—each led by an appointed member of the President’s Cabinet—carry out the day-to-day administration of the federal government. …

The Department of Labor oversees federal programs for ensuring a strong American workforce. These programs address job training, safe working conditions, minimum hourly wage and overtime pay, employment discrimination, and unemployment insurance.

[384] Webpage: “Final Rule: Overtime—Defining and Delimiting the Exemptions for Executive, Administrative, Professional, Outside Sales and Computer Employees Under the Fair Labor Standards Act.” U.S. Department of Labor. April 21, 2017 at <www.dol.gov>

On May 18, 2016, President Obama and Secretary Perez announced the publication of the Department of Labor’s final rule updating the overtime regulations, which will automatically extend overtime pay protections to over 4 million workers within the first year of implementation. This long-awaited update will result in a meaningful boost to many workers’ wallets, and will go a long way toward realizing President Obama’s commitment to ensuring every worker is compensated fairly for their hard work. …

Key Provisions of the Final Rule

The Final Rule focuses primarily on updating the salary and compensation levels needed for Executive, Administrative and Professional workers to be exempt. Specifically, the Final Rule:

Sets the standard salary level at the 40th percentile of earnings of full-time salaried workers in the lowest-wage Census Region, currently the South ($913 per week; $47,476 annually for a full-year worker). …

The effective date of the final rule is December 1, 2016.

[385] Webpage: “Fact Sheet: Proposed Rulemaking to Update the Regulations Defining and Delimiting the Exemptions for ‘White Collar’ Employees.” U.S. Department of Labor. Accessed April 21, 2017 at <www.dol.gov>

The Department is proposing to update the regulations governing which executive, administrative, and professional employees (white collar workers) are entitled to the Fair Labor Standards Act’s minimum wage and overtime pay protections. The Department last updated these regulations in 2004, and the current salary threshold for exemption is $455 per week ($23,660 per year). With this proposed rule, the Department seeks to update the salary level required for exemption to ensure that the FLSA’s intended overtime protections are fully implemented, and to simplify the identification of nonexempt employees, thus making the executive, administrative and professional employee exemption easier for employers and workers to understand and apply.

[386] Webpage: “Final Rule: Overtime—Defining and Delimiting the Exemptions for Executive, Administrative, Professional, Outside Sales and Computer Employees Under the Fair Labor Standards Act.” U.S. Department of Labor. April 21, 2017 at <www.dol.gov>

“The effective date of the final rule is December 1, 2016.”

[387] Webpage: “Important Information Regarding Recent Overtime Litigation in the U.S. District Court of Eastern District of Texas.” U.S. Department of Labor. Accessed April 21, 2017 at <www.dol.gov>

Important information regarding recent overtime litigation in the U.S. District Court of Eastern District of Texas

On November 22, 2016, U.S. District Court Judge Amos Mazzant granted an Emergency Motion for Preliminary Injunction and thereby enjoined the Department of Labor from implementing and enforcing the Overtime Final Rule on December 1, 2016. The case was heard in the United States District Court, Eastern District of Texas, Sherman Division (State of Nevada ET AL v. United States Department of Labor ET AL No: 4:16-CV-00731). The rule updated the standard salary level and provided a method to keep the salary level current to better effectuate Congress’s intent to exempt bona fide white collar workers from overtime protections.

On December 1, 2016, the Department of Justice on behalf of the Department of Labor filed a notice to appeal the preliminary injunction to the U.S. Circuit Court of Appeals for the Fifth Circuit. The Department has moved to expedite the appeal, which was approved by the Court.

Since 1940, the Department’s regulations have generally required each of three tests to be met for the FLSA’s executive, administrative, and professional (EAP) exemption to apply: (1) the employee must be paid a predetermined and fixed salary that is not subject to reduction because of variations in the quality or quantity of work performed (“salary basis test”); (2) the amount of salary paid must meet a minimum specified amount (“salary level test”); and (3) the employee’s job duties must primarily involve executive, administrative, or professional duties as defined by the regulations (“duties test”). The Department has always recognized that the salary level test works in tandem with the duties tests to identify bona fide EAP employees. The Department has updated the salary level requirements seven times since 1938.

The Department strongly disagrees with the decision by the court. The Department’s Overtime Final Rule is the result of a comprehensive, inclusive rule-making process, and we remain confident in the legality of all aspects of the rule.

For the latest news and updates on the Overtime Final Rule, subscribe to our mailing list.

[388] Article: “Texas Judge Strikes Down Obama Overtime Rule.” By John Bowden. The Hill, August 31, 2017. <thehill.com>

A federal judge in Texas has struck down a rule from the Department of Labor that would have extended overtime pay to more than 4 million workers, effectively erasing one of former President Obama’s biggest regulatory initiatives.

In the ruling, first reported by Bloomberg BNA, the judge wrote that the agency improperly looked at salaries instead of job descriptions when determining whether a worker should be eligible for overtime pay.

The judge, Obama-appointee Amos Mazzant, initially put the rule on hold last November.

[389] Article: “Justice Department Drops Appeal to Save Obama Overtime Rule.” By John Bowden. The Hill, September 5, 2017. <thehill.com>

“The Justice Department announced on Tuesday that it will not defend an Obama-era Labor Department rule that would have extended overtime benefits to more than 4 million workers after a federal judge struck it down last week.”

[390] Public Law 798: “Davis-Bacon Act.” 71st Congress. Signed into law by Herbert W. Hoover on March 3, 1931. <legisworks.org>

CHAP. 411.—An Act Relating to the rate of wages for laborers and mechanics employed on public buildings of the United States and the District of Columbia by contractors and subcontractors, and for other purposes.

Be it enacted by the Senate and House of Representatives of the United States of America in Congress assembled, That every contract in excess of $5,000 in amount, to which the United States or the District of Columbia is a party, which requires or involves the employment of laborers or mechanics in the construction, alteration, and/or repair of any public buildings of the United States or the District of Columbia within the geographical limits of the States of the Union or the District of Columbia, shall contain a provision to the effect that the rate of wage for all laborers and mechanics employed by the contractor or any subcontractor on the public buildings covered by the contract shall be not less than the prevailing rate of wages for work of a similar nature in the city, town, village, or other civil division of the State in which the public buildings are located, or in the District of Columbia if the public buildings are located there, and a further provision that in case any dispute arises as to what are the prevailing rates of wages for work of a similar nature applicable to the contract which can not be adjusted by the contracting officer, the matter shall be referred to the Secretary of Labor for determination and his decision thereon shall be conclusive on all parties to the contract : Provided, That in case of national emergency the President is authorized to suspend the provisions of this Act.

SEC. 2. This Act shall take effect thirty days after its passage but shall not affect any contract then existing or any contract that may thereafter be entered into pursuant to invitations for bids that are outstanding at the time of the passage of this Act.

Approved, March 3, 1931 .

[391] Public Law 718: “Fair Labor Standards Act of 1938.” 75th Congress. Signed into law by Franklin D. Roosevelt on June 25, 1938. <legisworks.org>

An Act

To provide for the establishment of fair labor standards in employments in and affecting interstate commerce, and for other purposes.

Be it enacted by the Senate and House of Representatives of the United States of America in Congress assembled, That this Act may be cited as the “Fair Labor Standards Act of 1938”.

Finding and Declaration of Policy

SEC. 2. (a) The Congress hereby finds that the existence, in industries engaged in commerce or in the production of goods for commerce, of labor conditions detrimental to the maintenance of the minimum standard of living necessary for health, efficiency, and general wellbeing of workers (1) causes commerce and the channels and instrumentalities of commerce to be used to spread and perpetuate such labor conditions among the workers of the several States ; (2) burdens commerce and the free flow of goods in commerce ; (3) constitutes an unfair method of competition in commerce ; (4) leads to labor disputes burdening and obstructing commerce and the free flow of goods in commerce ; and (5) interferes with the orderly and fair marketing of goods in commerce. (b) It is hereby declared to be the policy of this Act, through the exercise by Congress of its power to regulate commerce among the several States, to correct and as rapidly as practicable to eliminate the conditions above referred to in such industries without substantially curtailing employment or earning power.

Definitions

SEC. 3. As used in this Act—

(a) “Person” means an individual, partnership, association, corporation, business trust, legal representative, or any organized group of persons.

(b) “Commerce” means trade, commerce, transportation, transmission, or communication among the several States or from any State to any place outside thereof.

(c) “State” means any State of the United States or the District of Columbia or any Territory or possession of the United States.

(d) “Employer” includes any person acting directly or indirectly in the interest of an employer in relation to an employee but shall not include the United States or any State or political subdivision of a State, or any labor organization (other than when acting as an employer), or anyone acting in the capacity of officer or agent of such labor organization.

(e) “Employee” includes any individual employed by an employer.

(f) “Agriculture” includes farming in all its branches and among other things includes the cultivation and tillage of the soil, dairying, the production, cultivation, growing, and harvesting of any agricultural or horticultural commodities (including commodities defined as agricultural commodities in section 15 (g) of the Agricultural Marketing Act, as amended), the raising of livestock, bees, fur-bearing animals, or poultry, and any practices (including any forestry or lumbering operations) performed by a farmer or on a farm as an incident to or in conjunction with such farming operations, including preparation for market, delivery to storage or to market or to carriers for transportation to market.

(g) “Employ” includes to suffer or permit to work.

(h) “Industry” means a trade, business, industry, or branch thereof, or group of industries, in which individuals are gainfully employed.

(i) “Goods” means goods (including ships and marine equipment), wares, products, commodities, merchandise, or articles or subjects of commerce of any character, or any part or ingredient thereof, but does not include goods after their delivery into the actual physical possession of the ultimate consumer thereof other than a producer, manufacturer, or processor thereof.

(j) “Produced” means produced, manufactured, mined, handled, or in any other manner worked on in any State; and for the purposes of this Act an employee shall be deemed to have been engaged in the production of goods if such employee was employed in producing, manufacturing, mining, handling, transporting, or in any other manner working on such goods, or in any process or occupation necessary to the production thereof, in any State.

(k) “Sale” or “sell” includes any sale, exchange, contract to sell, consignment for sale, shipment for sale, or other disposition.

(1) “Oppressive child labor” means a condition of employment under which (1) any employee under the age of sixteen years is employed by an employer (other than a parent or a person standing in place of a parent employing his own child or a child in his custody under the age of sixteen years in an occupation other than manufacturing or mining) in any occupation, or (2) any employee between the ages of sixteen and eighteen years is employed by an employer in any occupation which the Chief of the Children’s Bureau in the Department of Labor shall find and by order declare to be particularly hazardous for the employment of children between such ages or detrimental to their health or well-being ; but oppressive child labor shall not be deemed to exist by virtue of the employment in any occupation of any person with respect to whom the employer shall have on file an unexpired certificate issued and held pursuant to regulations of the Chief of the Children’s Bureau certifying that such person is above the oppressive child-labor age. The Chief of the Children’s Bureau shall provide by regulation or by order that the employment of employees between the ages of fourteen and sixteen years in occupations other than manufacturing and mining shall not be deemed to constitute oppressive child labor if and to the extent that the Chief of the Children’s Bureau determines that such employment is confined to periods which will not interfere with their schooling and to conditions which will not interfere with their health and well-being.

(m) “Wage” paid to any employee includes the reasonable cost, as determined by the Administrator, to the employer of furnishing such employee with board, lodging, or other facilities, if such board, lodging, or other facilities are customarily furnished by such employer to his employees. …

Minimum Wages

SEC. 6. (a) Every employer shall pay to each of his employees who is engaged in commerce or in the production of goods for commerce wages at the following rates—

(1) during the first year from the effective date of this section, not less than 25 cents an hour,

(2) during the next six years from such date, not less than 30 cents an hour,

(3) after the expiration of seven years from such date, not less than 40 cents an hour, or the rate (not less than 30 cents an hour) prescribed in the applicable order of the Administrator issued under section 8, whichever is lower, and

(4) at any time after the effective date of this section, not less than the rate (not in excess of 40 cents an hour) prescribed in the applicable order of the Administrator issued under section 8.

(b) This section shall take effect upon the expiration of one hundred and twenty days from the date of enactment of the Act.

Approved, June 25, 1938.

[392] Public Law 718: “Fair Labor Standards Act of 1938.” 75st Congress. Signed into law by Franklin D. Roosevelt on June 25, 1938. <legisworks.org>

Section 6:

Minimum Wages

SEC. 6. (a) Every employer shall pay to each of his employees who is engaged in commerce or in the production of goods for commerce wages at the following rates—

(1) during the first year from the effective date of this section, not less than 25 cents an hour,

(2) during the next six years from such date, not less than 30 cents an hour,

(3) after the expiration of seven years from such date, not less than 40 cents an hour, or the rate (not less than 30 cents an hour) prescribed in the applicable order of the Administrator issued under section 8, whichever is lower, and

(4) at any time after the effective date of this section, not less than the rate (not in excess of 40 cents an hour) prescribed in the applicable order of the Administrator issued under section 8.

(b) This section shall take effect upon the expiration of one hundred and twenty days from the date of enactment of the Act.

Approved, June 25, 1938.

[393] Calculated with data from the webpage: “CPI Inflation Calculator.” United States Department of Labor, Bureau of Labor Statistics. Accessed June 15, 2017 at <www.bls.gov>

About the CPI Inflation Calculator

The CPI inflation calculator uses the Consumer Price Index for All Urban Consumers (CPI-U) U.S. city average series for all items, not seasonally adjusted. This data represents changes in the prices of all goods and services purchased for consumption by urban households. For the current year, the most recently published monthly index value is used. For previous years, the annual average value is used.

$0.25 in June of 1938 is equivalent to $4.34 in May of 2017

[394] Webpage: “Federal Minimum Wage Rates Under the Fair Labor Standards Act.” U.S. Department of Labor. Accessed February 6, 2017 at <www.dol.gov>

[395] Webpage: “Questions and Answers About the Minimum Wage.” U.S. Department of Labor, Wage and Hour Division. Accessed December 9, 2017 At <www.dol.gov>

Various minimum wage exceptions apply under specific circumstances to workers with disabilities, full-time students, youth under age 20 in their first 90 consecutive calendar days of employment, tipped employees and student-learners.

What is the minimum wage for workers who receive tips?

An employer may pay a tipped employee not less than $2.13 an hour in direct wages if that amount plus the tips received equal at least the federal minimum wage, the employee retains all tips and the employee customarily and regularly receives more than $30 a month in tips. If an employee’s tips combined with the employer’s direct wages of at least $2.13 an hour do not equal the federal minimum hourly wage, the employer must make up the difference.

Some states have minimum wage laws specific to tipped employees. When an employee is subject to both the federal and state wage laws, the employee is entitled to the provisions of each law which provide the greater benefits.

Must young workers be paid the minimum wage?

A minimum wage of $4.25 per hour applies to young workers under the age of 20 during their first 90 consecutive calendar days of employment with an employer, as long as their work does not displace other workers. After 90 consecutive days of employment or the employee reaches 20 years of age, whichever comes first, the employee must receive a minimum wage of $7.25 per hour effective July 24, 2009.

Other programs that allow for payment of less than the full federal minimum wage apply to workers with disabilities, full-time students, and student-learners employed pursuant to sub-minimum wage certificates. These programs are not limited to the employment of young workers.

What minimum wage exceptions apply to full-time students?

The Full-time Student Program is for full-time students employed in retail or service stores, agriculture, or colleges and universities. The employer that hires students can obtain a certificate from the Department of Labor which allows the student to be paid not less than 85% of the minimum wage. The certificate also limits the hours that the student may work to 8 hours in a day and no more than 20 hours a week when school is in session and 40 hours when school is out, and requires the employer to follow all child labor laws. Once students graduate or leave school for good, they must be paid $7.25 per hour effective July 24, 2009.

There are some limitations on the use of the full-time student program. For information on the limitations or to obtain a certificate, contact the Department of Labor’s Wage and Hour National Certification Team at 230 South Dearborn Street, Room 514, Chicago, Illinois 60604, telephone: 312-596-7195.

What minimum wage exceptions apply to student learners?

This program is for high school students at least 16 years old who are enrolled in vocational education (shop courses). The employer that hires the student can obtain a certificate from the Department of Labor which allows the student to be paid not less than 75% of the minimum wage, for as long as the student is enrolled in the vocational education program.

Employers interested in applying for a student learner certificate should contact the Department of Labor’s Wage and Hour National Certification Team at 230 South Dearborn Street, Room 514, Chicago, Illinois 60604, telephone: 312-596-7195.

Other programs that allow for payment of less than the full federal minimum wage apply to disabled workers and full-time students employed pursuant to sub-minimum wage certificates.

[396] Calculated with data from the report: “Characteristics of Minimum Wage Workers, 2016.” U.S. Bureau of Labor Statistics, April 2017. <www.bls.gov>

Page 3: “Table 1. Wage and Salary Workers Paid Hourly Rates with Earnings at or Below the Prevailing Federal Minimum Wage, by Selected Characteristics, 2016 Annual Averages.”

Page 31:

Technical Notes

The estimates in this report were obtained from the Current Population Survey (CPS), which provides information on the labor force, employment, and unemployment. The survey is conducted monthly for the U.S. Bureau of Labor Statistics (BLS) by the U.S. Census Bureau using a scientifically selected national sample of about 60,000 eligible households in all 50 states and the District of Columbia. The survey also provides data on earnings, which are based on one-fourth of the CPS monthly sample and are limited to wage and salary workers. All self-employed workers, both incorporated and unincorporated, are excluded from these earnings estimates. …

Concepts and definitions

The principal definitions used in connection with the estimates of minimum wage workers presented in this report are described briefly below.

Wage and salary workers. These are those age 16 and older who receive wages, salaries, commissions, tips, payments in kind, or piece rates on their sole or principal job. This group includes employees in both the private and public sectors. All self-employed workers are excluded whether or not their businesses are incorporated.

Workers paid by the hour. These are wage and salary workers who report that they are paid at an hourly rate on their job. Historically, workers paid an hourly wage have made up approximately three-fifths of all wage and salary workers. Estimates of workers paid by the hour include both full- and part-time workers unless otherwise specified.

Hourly earnings. Data are for wage and salary workers who are paid by the hour and refer to a person’s sole or principal job. Hourly earnings for hourly paid workers do not include overtime pay, commissions, or tips received.

Workers paid at or below the prevailing federal minimum wage. The estimates of the numbers of workers with reported earnings at or below the federal minimum wage pertain only to workers who are paid hourly rates. Salaried workers and the other nonhourly paid workers are excluded.

NOTE: An Excel file containing the data and calculations is available upon request.

[397] Report: “Characteristics of Minimum Wage Workers, 2016.” U.S. Department of Labor, Bureau of Labor Statistics, April 2017. <www.bls.gov>

Page 2:

The industry with the highest percentage of workers earning hourly wages at or below the federal minimum wage was leisure and hospitality (about 13 percent). Three-fifths of all workers paid at or below the federal minimum wage were employed in this industry, almost entirely in restaurants and other food services. For many of these workers, tips may supplement the hourly wages received. (See table 4.)

[398] Report: “Characteristics of Minimum Wage Workers, 2016.” U.S. Bureau of Labor Statistics, April 2017. <www.bls.gov>

Page 23: “Table 9. Wage and Salary Workers Paid Hourly Rates with Earnings at or Below the Prevailing Federal Minimum Wage, by Usual Hours Worked Per Week on Primary Job, 2016 Annual Averages.”

“Usual hours worked per week on primary job … Total, 16 years and older … 0 to 34 hours … Percent distribution … At or below minimum wage … Total [=] 53.7”

[399] Report: “The Effects of a Minimum-Wage Increase on Employment and Family Income.” Congressional Budget Office, February 2014. <www.cbo.gov>

Pages 2–3:

Effects of the $10.10 Option on Employment and Income. Once fully implemented in the second half of 2016, the $10.10 option would reduce total employment by about 500,000 workers, or 0.3 percent, CBO projects. As with any such estimates, however, the actual losses could be smaller or larger; in CBO’s assessment, there is about a two-thirds chance that the effect would be in the range between a very slight reduction in employment and a reduction in employment of 1.0 million workers (see Table 1).

Many more low-wage workers would see an increase in their earnings. Of those workers who will earn up to $10.10 under current law, most—about 16.5 million, according to CBO’s estimates—would have higher earnings during an average week in the second half of 2016 if the $10.10 option was implemented.1 Some of the people earning slightly more than $10.10 would also have higher earnings under that option, for reasons discussed below. Further, a few higher-wage workers would owe their jobs and increased earnings to the heightened demand for goods and services that would result from the minimum-wage increase.

The increased earnings for low-wage workers resulting from the higher minimum wage would total $31 billion, by CBO’s estimate.2 However, those earnings would not go only to low-income families, because many low-wage workers are not members of low-income families. Just 19 percent of the $31 billion would accrue to families with earnings below the poverty threshold, whereas 29 percent would accrue to families earning more than three times the poverty threshold, CBO estimates.3

Moreover, the increased earnings for some workers would be accompanied by reductions in real (inflation-adjusted) income for the people who became jobless because of the minimum-wage increase, for business owners, and for consumers facing higher prices. CBO examined family income overall and for various income groups, reaching the following conclusions:

• Once the increases and decreases in income for all workers are taken into account, overall real income would rise by $2 billion.

• Real income would increase, on net, by $5 billion for families whose income will be below the poverty threshold under current law, boosting their average family income by about 3 percent and moving about 900,000 people, on net, above the poverty threshold (out of the roughly 45 million people who are projected to be below that threshold under current law).

• Families whose income would have been between one and three times the poverty threshold would receive, on net, $12 billion in additional real income. About $2 billion, on net, would go to families whose income would have been between three and six times the poverty threshold.

• Real income would decrease, on net, by $17 billion for families whose income would otherwise have been six times the poverty threshold or more, lowering their average family income by 0.4 percent.

1 In addition to the people who became jobless, some workers earning less than $10.10 per hour and not covered by minimum-wage laws would also not have increased earnings.

2 All effects on income are reported for the second half of 2016; annualized (that is, multiplied by two); and presented in 2013 dollars.

3 Poverty thresholds vary with family size and composition; CBO projects that in 2016, the poverty threshold (in 2013 dollars) will be about $18,700 for a family of three and $24,100 for a family of four.

[400] Report: “Characteristics of Minimum Wage Workers, 2016.” U.S. Bureau of Labor Statistics, April 2017. <www.bls.gov>

Page 25: “Table 10. Wage and Salary Workers Paid Hourly Rates with Earnings at or Below Prevailing Federal Minimum Wage, by Gender, 1979–2015 Annual Averages.”

Page 31:

Technical Notes

The estimates in this report were obtained from the Current Population Survey (CPS), which provides information on the labor force, employment, and unemployment. The survey is conducted monthly for the U.S. Bureau of Labor Statistics (BLS) by the U.S. Census Bureau using a scientifically selected national sample of about 60,000 eligible households in all 50 states and the District of Columbia. The survey also provides data on earnings, which are based on one-fourth of the CPS monthly sample and are limited to wage and salary workers. All self-employed workers, both incorporated and unincorporated, are excluded from these earnings estimates. …

Concepts and definitions

The principal definitions used in connection with the estimates of minimum wage workers presented in this report are described briefly below.

Wage and salary workers. These are those age 16 and older who receive wages, salaries, commissions, tips, payments in kind, or piece rates on their sole or principal job. This group includes employees in both the private and public sectors. All self-employed workers are excluded whether or not their businesses are incorporated.

Workers paid by the hour. These are wage and salary workers who report that they are paid at an hourly rate on their job. Historically, workers paid an hourly wage have made up approximately three-fifths of all wage and salary workers. Estimates of workers paid by the hour include both full- and part-time workers unless otherwise specified.

Hourly earnings. Data are for wage and salary workers who are paid by the hour and refer to a person’s sole or principal job. Hourly earnings for hourly paid workers do not include overtime pay, commissions, or tips received.

Workers paid at or below the prevailing federal minimum wage. The estimates of the numbers of workers with reported earnings at or below the federal minimum wage pertain only to workers who are paid hourly rates. Salaried workers and the other nonhourly paid workers are excluded.

[401] Webpage: “David Neumark: Curriculum Vitae.” University of California, Irvine. Accessed March 27, 2017 at <www.socsci.uci.edu>

[402] Webpage: “J.M. Ian Salas: Curriculum Vitae.” J.M Ian Salas personal website. Accessed March 27, 2017 at <sites.google.com>

[403] Webpage: “Meet the Economists: William L. Wascher.” Board of Governors of the Federal Reserve System. Accessed March 27, 2017 at <www.federalreserve.gov>

[404] Working paper: “Revisiting the Minimum Wage-Employment Debate: Throwing Out the Baby with the Bathwater?” By David Neumark, J.M. Ian Salas, and William Wascher. Institute for the Study of Labor, January 2013. <ftp.iza.org>

Page 1: “Debates about the economic effects and the merits of the minimum wage date back at least as far as the establishment of the Department of Labor as a cabinet-level agency in 1913.”

Pages 2–3:

Over time, empirical analyses, especially the time-series studies conducted in the 1960s and 1970s, increasingly found that minimum wages tended to reduce employment among teenagers, who were viewed as a proxy for low-skilled labor more generally. A famous paper by Charles Brown, Curtis Gilroy, and Andrew Kohen, published in 1982, surveyed the existing literature on minimum wages and established the “consensus” that a 10 percent increase in the minimum wage would reduce teenage employment by 1 to 3 percent (Brown et al., 1982). Following that study, economists began to coalesce around the idea that minimum wages have adverse effects on low-skilled employment.

That consensus turned out to be relatively short-lived. After a decade of near-silence, the debate over the employment effects of the minimum wage reemerged in the early 1990s with the publication of a special issue of the Industrial and Labor Relations Review (ILRR). This issue featured four studies that used different analytical approaches and that took advantage of the increasing divergence of minimum wages at the state level to estimate the employment effects of minimum wages. These studies, which formed the basis for what is sometimes termed the “new minimum wage research,” were diverse in their findings, ranging from dis-employment effects similar to the earlier consensus (Neumark and Wascher 1992), to no effect on employment (Card 1992a) to a positive effect of the minimum wage on employment (Card 1992b; Katz and Krueger 1992).

[405] Paper: “Minimum Wages and Employment.” By David Neumark and William Wascher. Foundations and Trends in Microeconomics, March 29, 2007. <www.nowpublishers.com>

Page 163:

Our lengthy review of the new minimum wage research documents the wide range of estimates of the effects of the minimum wage on employment, especially when compared to the review of the earlier literature by Brown et al. (1982). For example, few of the studies in the Brown et al. survey were outside of the consensus range of −0.1 to −0.3 for the elasticity of teenage employment with respect to the minimum wage. In contrast, even limiting the sample of studies to those focused on the effects of the minimum wage of teenagers in the United States, the range of studies comprising the new minimum wage research extends from near −1 to above zero.

[406] Paper: “Minimum Wages and Employment.” By David Neumark and William Wascher. Foundations and Trends in Microeconomics, March 29, 2007. <www.nowpublishers.com>

Pages 163–164:

Nonetheless, the oft-stated assertion that the new minimum wage research fails to support the conclusion that the minimum wage reduces the employment of low-skilled workers is clearly incorrect. Indeed, in our view, the preponderance of the evidence points to dis-employment effects. For example, the studies surveyed in this monograph correspond to 102 entries in our summary tables.1 Of these, nearly two thirds give a relatively consistent (although by no means always statistically significant) indication of negative employment effects of minimum wages, while only eight give a relatively consistent indication of positive employment effects

1 We do not include every single paper we have discussed. In particular, a few papers that use very similar data and estimators to other papers included in the tables, but that largely comment on or replicate the latter, or present a narrower set of estimates, are not included.

[407] Paper: “Minimum Wages and Employment.” By David Neumark and William Wascher. Foundations and Trends in Microeconomics, March 29, 2007. <www.nowpublishers.com>

Page 164: “Moreover, when researchers focus on the least-skilled groups most likely to be adversely affected by minimum wages, the evidence for disemployment effects seems especially strong.”

[408] Paper: “Minimum Wages and Employment.” By David Neumark and William Wascher. Foundations and Trends in Microeconomics, March 29, 2007. <www.nowpublishers.com>

Page 164: “In contrast, we see very few—if any—cases where a study provides convincing evidence of positive employment effects of minimum wages, especially among the studies that focus on broader groups for which the competitive model predicts dis-employment effects.”

[409] Webpage: “Minimum Wage Laws in the States—January 1, 2007.” Wage and Hour Division, U.S. Department of Labor. Last revised January 1, 2017. <www.dol.gov>

Consolidated State Minimum Wage Update Table

(Effective Date: 01/01/2017)

Greater than federal MW

Equals federal MW of $7.25

Less than federal MW

No MW Required

AK–$9.80

IA

GA–$5.15

AL

AR–$8.50

ID

WY–$5.15

LA

AZ–$10.00

IN

MS

CA–$10.50

KS

SC

CO–$9.30

KY

TN

CT–$10.10

NC

DC–$11.50

ND

DE–$8.25

NH

FL–$8.10

OK

HI–$9.25

PA

IL–$8.25

TX

MA–$11.00

UT

MD–$8.75

VA

ME–$9.00 (effective 1/7/17)

WI

MI–$8.90

CA–$10.50

MN–$9.50

MO–$7.70

MT–$8.15

NE–$9.00

NJ–$8.44

NM–$7.50

NY–$9.70

NV–$8.25

OH–$8.15

OR–$9.75

RI–$9.60

SD–$8.65

VT–$10.00

WA–$11.00

WV–$8.75

29 States + DC

14 States

2 States

5 States

• The state minimum wage rate requirements, or lack thereof, are generally controlled by legislative activities within the individual states.

• Federal minimum wage law supersedes state minimum wage laws where the federal minimum wage is greater than the state minimum wage. In those states where the state minimum wage is greater than the federal minimum wage, the state minimum wage prevails.

• There are 2 states than have a minimum wage set lower than the federal minimum wage. There are 29 states plus the District of Columbia with minimum wage rates set higher than the federal minimum wage. There are 14 states that have a minimum wage requirement that is the same as the federal minimum wage requirement. The remaining 5 states do not have an established minimum wage requirement.

• The District of Columbia has the highest minimum wage at $11.50/hour. The states of Georgia and Wyoming have the lowest minimum wage ($5.15/hour) of the 45 states that have a minimum wage requirement.

• Note: There are 12 states (AK, AZ, CO, FL, MO, MT, NJ, NV, OH, OR, SD, and WA) that have minimum wages that are linked to a consumer price index. As a result of this linkage, the minimum wages in these states are normally increased each year, generally around January 1st. The exception is Nevada which adjusts in the month of July each year. Effective January 1, 2017, seven (7) of the 12 states increased their respective minimum wages.

Prepared By:

Division of Communications

Wage and Hour Division

U.S. Department of Labor

This document was last revised in January 1, 2017.

The Wage and Hour Division tries to ensure that the information on this page is accurate but individuals should consult the relevant state labor office for official information.

[410] Webpage: “Minimum Wage.” U.S. Department of Labor. Accessed April 21, 2017 at <www.dol.gov>

The federal minimum wage for covered nonexempt employees is $7.25 per hour effective July 24, 2009. The federal minimum wage provisions are contained in the Fair Labor Standards Act (FLSA). Many states also have minimum wage laws. In cases where an employee is subject to both the state and federal minimum wage laws, the employee is entitled to the higher of the two minimum wages.

The FLSA does not provide wage payment or collection procedures for an employee’s usual or promised wages or commissions in excess of those required by the FLSA. However, some states do have laws under which such claims (sometimes including fringe benefits) may be filed.

The Department of Labor’s Wage and Hour Division administers and enforces the federal minimum wage law.

[411] Article: “L.A. Labor Leaders Seek Minimum Wage Exemption for Firms with Union Workers.” By Peter Jamison, David Zahniser and Emily Alpert Reyes. Los Angeles Times, May 26, 2015. <www.latimes.com>

Labor leaders, who were among the strongest supporters of the citywide minimum wage increase approved last week by the Los Angeles City Council, are advocating last-minute changes to the law that could create an exemption for companies with unionized workforces.

The push to include an exception to the mandated wage increase for companies that let their employees collectively bargain was the latest unexpected detour as the city nears approval of its landmark legislation to raise the minimum wage to $15 an hour by 2020. …

But Rusty Hicks, who heads the county Federation of Labor and helps lead the Raise the Wage coalition, said Tuesday night that companies with workers represented by unions should have leeway to negotiate a wage below that mandated by the law.

“With a collective bargaining agreement, a business owner and the employees negotiate an agreement that works for them both. The agreement allows each party to prioritize what is important to them,” Hicks said in a statement. “This provision gives the parties the option, the freedom, to negotiate that agreement. And that is a good thing.”

[412] Calculated with data from:

a) Dataset: “Table 6.2D. Compensation of Employees by Industry [Millions of Dollars].” United States Department of Commerce, Bureau of Economic Analysis. Last revised August 3, 2017. <www.bea.gov>

Line item 86: “Government … 2016 [=] 1,909,462”

b) Dataset: “Average Number of People per Household, by Race and Hispanic Origin, Marital Status, Age, and Education of Householder: 2016.” U.S. Census Bureau, November 2016. <www.census.gov>

“Total households [=] 125,819,000”

CALCULATION: $1,909,462,000,000 government employee compensation / 125,819,000 households = $15,176 per household

NOTE: As documented in the next five footnotes, this data on government employee compensation:

  • accounts for defined benefit pensions benefits “as employees earn them, rather than when employers actually make cash payments to pension plans.”
  • does not include the unfunded liabilities of retirement non-pension benefits (like health insurance). It does, however, include such spending for current retirees.

[413] Webpage: “What Changes Were Made to Pensions During the 2013 Comprehensive Revision, and How Have the Changes Affected Private, Federal, and State and Local Compensation?” U.S. Bureau of Economic Analysis, July 31, 2013. <www.bea.gov>

BEA changed its method for recording the transactions of defined benefit pension plans from a cash accounting basis to an accrual accounting basis as part of the comprehensive revision of the national income and product accounts (NIPAs) released on July 31, 2013. This improvement reflects the most recent international guidelines for the compilation of national accounts—the System of National Accounts 2008 (2008 SNA), which recommends an accrual-based treatment of defined benefit pension plans.

Defined benefit plans provide benefits during retirement based on a formula that typically depends on an employee’s length of service and average pay among other factors. The promised benefit entitlements tend to grow in a relatively smooth manner, whereas employers’ cash contributions may be volatile or sporadic. Accrual accounting is preferred over cash accounting for compiling national accounts because it aligns production with the incomes earned from that production and records both in the same period; cash accounting, on the other hand, reflects incomes when paid, regardless of when they were earned.  Thus, the accrual accounting method better reflects the relatively smooth manner in which benefits are earned by employees each period as a result of the work they perform.

The new treatment applies to all defined benefit pension plans—private, federal government, and state and local government—and this change resulted in revisions to BEA’s estimates of private, federal, and state and local compensation.

[414] Article: “Changes to How the U.S. Economy is Measured Roll Out July 31.” U.S. Bureau of Economic Analysis, July 23, 2013. <blog.bea.gov>

“On July 31, we will switch from a cash accounting method to an accrual accounting method to measure the transactions of defined benefit pension plans. That means we will count the benefits as employees earn them, rather than when employers actually make cash payments to pension plans.”

[415] Report: “Preview of the 2013 Comprehensive Revision of the National Income and Product Accounts: Changes in Definitions and Presentations: Changes in Definitions and Presentations.” By Shelly Smith and others. U.S. Bureau of Economic Analysis, March 2013. <www.bea.gov>

Page 25: “With this comprehensive revision, estimates of wages and salaries that are a component of personal income will be presented on an accrual basis back to 1929.”

[416] Email from the U.S. Bureau of Economic Analysis to Just Facts, March 19, 2015.

“Retiree health care benefits (which are separate from pensions) are treated on a cash basis and are effectively included in the compensation of current workers.”

[417] Webpage: “What Is Included in Federal Government Employee Compensation?” U.S. Bureau of Economic Analysis. Accessed November 17, 2016 at <www.bea.gov>

“The contributions for employee health insurance consist of the federal share of premium payments to private health insurance plans for current employees and retirees.”

[418] Calculated with data from:

a) Dataset: “Federal Government Civilian Employment and Payroll Data, March 2014.” U.S. Census Bureau, January 8, 2016. <www.census.gov>

“Total Employment … United States … 2014 [=] 2,700,468 … [This] includes the civilian employees of all the Federal Government agencies (except the Central Intelligence Agency, the National Security Agency, and the Defense Intelligence Agency).”

b) Dataset: “State Government Employment and Payroll Data, March 2014.” U.S. Census Bureau, January 8, 2016. <www.census.gov>

“Total March Full-Time and Part-Time Employment … United States … Year … 2014 [=] 5,335,707”

c) Dataset: “Local Government Employment and Payroll Data, March 2014.” U.S. Census Bureau, January 8, 2016. <www.census.gov>

“Total March Full-Time and Part-Time Employment … United States … Year … 2014 [=] 13,894,745”

d) Dataset: “Counts of Active Duty and Reserve Service Members and APF Civilians: By Location Country, Personnel Category, Service and Component, as of September 30, 2014.” U.S. Department of Defense, November 2016. <www.dmdc.osd.mil>

“Active Duty … Grand Total [=] 1,132,938”

e) Dataset: “LNS12000000. [Civilian] Employment Level.” U.S. Department of Labor, Bureau of Labor Statistics. Accessed March 24, 2017. <data.bls.gov>

“March 2014 [=] 145,715 (thousands)”

CALCULATIONS:

  • 2,700,468 civilian federal employees + 5,335,707 state government employees + 13,894,745 local government employees + 1,132,938 active duty military employees = 23,063,858 government employees.
  • 23,063,858 government employees / (145,715,000 civilian employees + 1,132,938 active duty military employees) = 15.7%

[419] Report: “Comparing the Compensation of Federal and Private-Sector Employees, 2011 to 2015.” U.S. Congressional Budget Office, April 2017. <www.cbo.gov>

Page 1: “Specifically, in its analysis, CBO sought to account for differences in individuals’ level of education, years of work experience, occupation, size of employer, geographic location (region of the country and urban or rural location), veteran status, and various demographic characteristics (age, sex, race, ethnicity, marital status, immigration status, and citizenship).”

Page 3: “Overall, the federal government paid 17 percent more in total compensation than it would have if average compensation had been comparable with that in the private sector, after accounting for certain observable characteristics of workers.”

Page 4: “CBO’s results apply to the cost of employing full-time, full-year workers. The analysis focuses on those workers—who accounted for about 94 percent of the total hours worked by federal employees from 2011 through 2015—because more-accurate data are available for them than for other workers.”

Page 5: “This analysis does not include military personnel or employees of self-financing government enterprises such as the Postal Service; federal contractors are included as private-sector workers.”

Page 11: “Table 2. Federal and Private-Sector Wages, by Level of Educational Attainment … Average Wages (2015 dollars per hour) … Percentage Difference Between Averages”

Page 14: “Table 3. Federal and Private-Sector Benefits, by Level of Educational Attainment … Average Wages (2015 dollars per hour) … Percentage Difference Between Averages”

Page 16: “Table 4. Federal and Private-Sector Total Compensation, by Level of Educational Attainment … Average Wages (2015 dollars per hour) … Percentage Difference Between Averages”

[420] Paper: “Two Faces of Union Voice in the Public Sector.” By Morley Gunderson. Journal of Labor Research, Summer 2005. <link.springer.com>

Page 398: “The lower resistance to unionization on the part of public sector managers reflects the fact that the survival of public sector organizations is not jeopardized by unions flexing their muscle. This is in contrast to private sector firms—and increasingly so under global competition.”

Page 399: “The degree of unionization in the public sector is simply not disciplined the same as in the private sector by such forces as the threat of bankruptcy or plant closing or moving offshore, or by competitive pressures to contain costs to be profitable, or by the need for managerial flexibility.”

Page 404:

In the private sector, however, the negative monopoly face of unions has been increasingly constrained by competitive market forces such as globalization and trade liberalization as well as by the industrial restructuring to services and the information economy. Rents are obviously harder to obtain when there are fewer rents on the bargaining table. There is little survival value to pricing yourself out of the market now that market forces are more prominent. In such a private sector environment, unions have generally declined, strikes have dissipated, and managerial prerogatives have been enhanced.

[421] Paper: “Card-Check Laws and Public-Sector Union Membership in the States.” By Timothy D. Chandler and Rafael Gely. Labor Studies Journal, December 2011. Pages 445–459. <lsj.sagepub.com>

Page 456: “This concern about employer hostility has been traditionally associated with private-sector employers, as the conventional wisdom has been that public-sector employees face a more favorable organizing environment, largely due to the lack of competitive pressures, a profit motive, or threat of bankruptcy for public-sector employers (Gunderson 2005).”

[422] Entry: “inelastic.” American Heritage Dictionary of the English Language (5th edition). Houghton Mifflin Harcourt, 2011. <www.thefreedictionary.com>

“2. Economics Of, relating to, or being a good for which changes in price have little effect on the quantity demanded or supplied: the inelastic demand for cigarettes.”

[423] Ruling 431 U.S. 209: Abood v. Detroit Board of Education. U.S. Supreme Court, May 23, 1977. Decided 9–0 (with three separate concurrences from four Justices, who sometimes expressed opposing views to the Court’s opinion). <www.law.cornell.edu>

NOTE: This portion of the ruling was not disputed by any of the Justices.

The appellants’ second argument is that in any event collective bargaining in the public sector is inherently “political” and thus requires a different result under the First and Fourteenth Amendments. This contention rests upon the important and often-noted differences in the nature of collective bargaining in the public and private sectors.24 A public employer, unlike his private counterpart, is not guided by the profit motive and constrained by the normal operation of the market. Municipal services are typically not priced, and where they are they tend to be regarded as in some sense “essential” and therefore are often price-inelastic. Although a public employer, like a private one, will wish to keep costs down, he lacks an important discipline against agreeing to increases in labor costs that in a market system would require price increases. A public-sector union is correspondingly less concerned that high prices due to costly wage demands will decrease output and hence employment.

The government officials making decisions as the public “employer” are less likely to act as a cohesive unit than are managers in private industry, in part because different levels of public authority department managers, budgetary officials, and legislative bodies are involved, and in part because each official may respond to a distinctive political constituency. And the ease of negotiating a final agreement with the union may be severely limited by statutory restrictions, by the need for the approval of a higher executive authority or a legislative body, or by the commitment of budgetary decisions of critical importance to others.

Finally, decisionmaking by a public employer is above all a political process. The officials who represent the public employer are ultimately responsible to the electorate, which for this purpose can be viewed as comprising three overlapping classes of voters; taxpayers, users of particular government services, and government employees. Through exercise of their political influence as part of the electorate, the employees have the opportunity to affect the decisions of government representatives who sit on the other side of the bargaining table. Whether these representatives accede to a union’s demands will depend upon a blend of political ingredients, including community sentiment about unionism generally and the involved union in particular, the degree of taxpayer resistance, and the views of voters as to the importance of the service involved and the relation between the demands and the quality of service. It is surely arguable, however, that permitting public employees to unionize and a union to bargain as their exclusive representative gives the employees more influence in the decisionmaking process than is possessed by employees similarly organized in the private sector. …

24 See, e. g., K. Hanslowe, The Emerging Law of Labor Relations in Public Employment (1967); H. Wellington & R. Winter, Jr., The Unions and the Cities (1971); Hildebrand, The Public Sector, in J. Dunlop and N. Chamberlain (eds.), Frontiers of Collective Bargaining 125–154 (1967); Rehmus, Constraints on Local Governments in Public Employee Bargaining, 67 Mich.L.Rev. 919 (1969); Shaw & Clark, The Practical Differences Between Public and Private Sector Collective Bargaining, 19 U.C.L.A.L.Rev. 867 (1972); Smith, State and Local Advisory Reports on Public Employment Labor Legislation: A Comparative Analysis, 67 Mich.L.Rev. 891 (1969); Summers, Public Employee Bargaining: A Political Perspective, 83 Yale L.J. 1156 (1974); Project, Collective Bargaining and Politics in Public Employment, 19 U.C.L.A.L.Rev. 887 (1972). The general description in the text of the differences between private- and public-sector collective bargaining is drawn from these sources.

[424] News release: “Where is the Wealth? Median Household Net Worth by Quintile.” U.S. Census Bureau, August 21, 2014. <www.census.gov>

Net Worth (wealth) is defined as the sum of the market value of assets owned by every member of the household minus liabilities owed.

Key assets include: the value of a household’s home, retirement accounts, stocks and mutual fund shares, and interest-earning assets (interest-earning checking accounts, savings accounts, etc.).

Key liabilities include: mortgages on a household’s home, credit card debt, student loan debt, and medical debt not covered by insurance.

[425] Paper: “A Multi-dimensional Measure of Economic Well-Being for the U.S.: The Material Condition Index.” By Thesia Garner and Kathleen S. Short. U.S. Department of Labor, Bureau of Labor Statistics, October 2013. <www.bls.gov>

Page 295:

The definition of wealth, or net worth, follo