Income and Wealth Inequality
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Nicholas Bloom -
Raj Chetty -
Emmanuel Saez
Leaders: Nicholas Bloom, Raj Chetty, Emmanuel Saez
The CPI is home to some of the country’s most influential analyses of the income and wealth distribution. The purpose of the Income and Wealth RG is to monitor the ongoing takeoff in income inequality, to better understand its sources, and to analyze its implications for labor market performance, educational attainment, mobility, and more. The following is a sampling of the CPI’s research projects within this area.
Trends in income and wealth inequality: What are the key trends in U.S. income and wealth inequality? The U.S. increasingly looks to Emmanuel Saez and his research team for the latest data on U.S. economic inequality.
Distributional National Accounts: In an ambitious infrastructural project, Emmanuel Saez and his team are building a “Distributional National Accounts” based on tax returns, a data set that will eliminate the current gap between (a) national accounts data based on economic aggregates and (b) inequality analysis that uses micro-level tax data to examine the distribution of income but is not consistent with national aggregates. This new data set will in turn make it possible to evaluate the extent to which economic growth, which has long been represented as a preferred poverty-reduction approach, is indeed delivering on that objective.
The rise of between-firm inequality: How much of the rise in earnings inequality can be attributed to increasing between-firm dispersion in the average wages they pay? This question can be addressed by constructing a matched employer-employee data set for the United States using administrative records.
Rent and inequality: It is increasingly fashionable to argue that “rent” accounts for much of the takeoff in income inequality. The Current Population Survey can be used to assess whether this claim is on the mark.
Featured Examples
Income And Wealth - CPI Research
| Title | Author | Media | |
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| The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers | Cody Cook, Rebecca Diamond, Jonathan Hall, John A. List, Paul Oyer |
The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare DriversAuthor: Cody Cook, Rebecca Diamond, Jonathan Hall, John A. List, Paul OyerPublisher: NBER Date: 06/2018 The growth of the “gig” economy generates worker flexibility that, some have speculated, will favor women. We explore this by examining labor supply choices and earnings among more than a million rideshare drivers on Uber in the U.S. We document a roughly 7% gender earnings gap amongst drivers. We completely explain this gap and show that it can be entirely attributed to three factors: experience on the platform (learning-by-doing), preferences over where to work (driven largely by where drivers live and, to a lesser extent, safety), and preferences for driving speed. We do not find that men and women are differentially affected by a taste for specific hours, a return to within-week work intensity, or customer discrimination. Our results suggest that there is no reason to expect the “gig” economy to close gender differences. Even in the absence of discrimination and in flexible labor markets, women’s relatively high opportunity cost of non-paid-work time and gender-based differences in preferences and constraints can sustain a gender pay gap. |
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| Distributional National Accounts: Methods and Estimates for the United States | Thomas Piketty, Emmanuel Saez, Gabriel Zucman |
Distributional National Accounts: Methods and Estimates for the United StatesAuthor: Thomas Piketty, Emmanuel Saez, Gabriel ZucmanPublisher: Quarterly Journal of Economics Date: 05/2018 This article combines tax, survey, and national accounts data to estimate the distribution of national income in the United States since 1913. Our distributional national accounts capture 100% of national income, allowing us to compute growth rates for each quantile of the income distribution consistent with macroeconomic growth. We estimate the distribution of both pretax and posttax income, making it possible to provide a comprehensive view of how government redistribution affects inequality. Average pretax real national income per adult has increased 60% from 1980 to 2014, but we find that it has stagnated for the bottom 50% of the distribution at about $16,000 a year. The pretax income of the middle class—adults between the median and the 90th percentile—has grown 40% since 1980, faster than what tax and survey data suggest, due in particular to the rise of tax-exempt fringe benefits. Income has boomed at the top. The upsurge of top incomes was first a labor income phenomenon but has mostly been a capital income phenomenon since 2000. The government has offset only a small fraction of the increase in inequality. The reduction of the gender gap in earnings has mitigated the increase in inequality among adults, but the share of women falls steeply as one moves up the labor income distribution, and is only 11% in the top 0.1% in 2014. |
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| Inequality of Educational Opportunity? Schools as Mediators of the Intergenerational Transmission of Income | Jesse Rothstein |
Inequality of Educational Opportunity? Schools as Mediators of the Intergenerational Transmission of IncomeAuthor: Jesse RothsteinPublisher: NBER Date: 04/2018 Chetty et al. (2014b) show that children from low-income families achieve higher adult incomes, relative to those from higher income families, in some commuting zones (CZs) than in others. I investigate whether children’s educational outcomes help to explain the between-CZ differences. I find little evidence that the quality of schools is a key mechanism driving variation in intergenerational mobility. While CZs with stronger intergenerational income transmission have somewhat stronger transmission of parental income to children’s educational attainment and achievement, on average, neither can explain a large share of the between-CZ variation. Marriage patterns explain two-fifths of the variation in income transmission, human capital accumulation and returns to human capital each explain only one-ninth, and the remainder of the variation (about one-third) reflects differences in earnings between children from high- and low-income families that are not mediated by human capital. This points to job networks and the structure of local labor and marriage markets, rather than the education system, as likely factors influencing intergenerational economic mobility. |
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| State of the Union 2018: Earnings | Emmanuel Saez |
State of the Union 2018: EarningsAuthor: Emmanuel SaezPublisher: Stanford Center on Poverty and Inequality Date: 03/2018 Gender wage gaps, as conventionally measured, understate the extent of gender inequality in the labor market. When gender differences in wages are examined in conjunction with gender differences in labor force participation, fringe benefits, and self-employment income, men’s average labor earnings are 75 percent higher than women’s. Under this fuller accounting, women thus earn 57 cents for each dollar earned by men. Although women have come to comprise almost 50 percent of the formal labor market, their representation in top labor income groups has risen very slowly. In the most recent available data, just 16 percent of the top 1 percent of labor income earners are women. |
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| Increasing Inequality in Parent Incomes and Children’s Schooling | Greg J. Duncan, Ariel Kalil, Kathleen M. Ziol-Guest |
Increasing Inequality in Parent Incomes and Children’s SchoolingAuthor: Greg J. Duncan, Ariel Kalil, Kathleen M. Ziol-GuestPublisher: Demography Date: 08/2017 Income inequality and the achievement test score gap between high- and low-income children increased dramatically in the United States beginning in the 1970s. This article investigates the demographic (family income, mother’s education, family size, two-parent family structure, and age of mother at birth) underpinnings of the growing income-based gap in schooling using data from the Panel Study of Income Dynamics. Across 31 cohorts, we find that increases in the income gap between high- and low-income children account for approximately three-quarters of the increasing gap in completed schooling, one-half of the gap in college attendance, and one-fifth of the gap in college graduation. We find no consistent evidence of increases in the estimated associations between parental income and children’s completed schooling. Increasing gaps in the two-parent family structures of high- and low-income families accounted for relatively little of the schooling gap because our estimates of the (regression-adjusted) associations between family structure and schooling were surprisingly small for much of our accounting period. On the other hand, increasing gaps in mother’s age at the time of birth accounts for a substantial portion of the increasing schooling gap: mother’s age is consistently predictive of children’s completed schooling, and the maternal age gap for children born into low- and high-income families increased considerably over the period. |
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income and wealth - CPI Affiliates
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Moshe Semyonov |
Bernard and Audre Rapoport Chair Professor of the Sociology of Labor, Tel Aviv University; Professor of Sociology, University of Illinois at Chicago |
University of Illinois at Chicago and Tel Aviv University |
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Henryk Domanski |
Professor, Director, Institute of Philosophy and Sociology |
Polish Academy of Sciences |
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Dennis Gilbert |
Professor of Sociology Emeritus; Lecturer in Sociology |
Hamilton College |
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Tak Wing Chan |
Professor of Quantitative Social Science |
UCL Institute of Education |
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Nan Dirk De Graaf |
Professor and Official Fellow, Department of Sociology, Nuffield College |
University of Oxford |
Pages
Income And Wealth - Other Research
| Title | Author | Media | |
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| Household Wealth Trends in the United States, 1962 to 2016: Has Middle Class Wealth Recovered? | Edward N. Wolff |
Household Wealth Trends in the United States, 1962 to 2016: Has Middle Class Wealth Recovered?Author: Edward N. WolffPublisher: NBER Date: 11/2017 Asset prices plunged between 2007 and 2010 but then rebounded from 2010 to 2016. The most telling finding is that median wealth plummeted by 44 percent over years 2007 to 2010. The inequality of net worth, after almost two decades of little movement, went up sharply from 2007 to 2010, and relative indebtedness for the middle class expanded. The sharp fall in median net worth and the rise in overall wealth inequality over these years are largely traceable to the high leverage of middle class families and the high share of homes in their portfolio. Mean and median wealth rebounded from 2010 to 2016, by 17 and 28 percent, respectively. While mean wealth surpassed its previous peak in 2007, median wealth was still down by 34 percent. More than 100 percent of the recovery in both was due to a high return on wealth but this factor was offset by negative savings. Relative indebtedness continued to fall for the middle class from 2010 to 2016, and wealth inequality increased somewhat. The racial and ethnic disparity in wealth holdings widened considerably between 2007 and 2016, and the wealth of households under age 45 declined in relative terms. |
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| Income and Poverty in the United States: 2016 | Jessica L. Semega, Kayla R. Fontenot, Melissa A. Kollar |
Income and Poverty in the United States: 2016Author: Jessica L. Semega, Kayla R. Fontenot, Melissa A. KollarPublisher: U.S. Census Bureau Date: 09/2017 Summary of findings: Real median household income increased 3.2 percent between 2015 and 2016.2 This is the second consecutive annual increase in median household income. The number of full-time, year-round workers increased by 2.2 million in 2016. The 2016 female-to-male earnings ratio was 0.805, a 1.1 percent increase from the 2015 ratio. This is the first time the female-to-male earnings ratio has experienced an annual increase since 2007. The official poverty rate decreased by 0.8 percentage points between 2015 and 2016. At 12.7 percent, the 2016 poverty rate is not statistically different from 2007 (12.5 percent), the year before the most recent recession. The number of people in poverty fell by 2.5 m |
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| Consumption and Income Inequality in the U.S. Since the 1960s | Bruce D. Meyer, James X. Sullivan |
Consumption and Income Inequality in the U.S. Since the 1960sAuthor: Bruce D. Meyer, James X. SullivanPublisher: NBER Date: 08/2017 Official income inequality statistics indicate a sharp rise in inequality over the past five decades. These statistics do not accurately reflect inequality because income is poorly measured, particularly in the tails of the distribution, and current income differs from permanent income, failing to capture the consumption paid for through borrowing and dissaving and the consumption of durables such as houses and cars. We examine income inequality between 1963 and 2014 using the Current Population Survey and consumption inequality between 1960 and 2014 using the Consumer Expenditure Survey. We construct improved measures of consumption, focusing on its well-measured components that are reported at a high and stable rate relative to national accounts. While overall income inequality (as measured by the 90/10 ratio) rose over the past five decades, the rise in overall consumption inequality was small. The patterns for the two measures differ by decade, and they moved in opposite directions after 2006. Income inequality rose in both the top and bottom halves of the distribution, but increases in consumption inequality are only evident in the top half. The differences are also concentrated in single parent families and single individuals. Although changing demographics can account for some of the changes in consumption inequality, they account for little of the changes in income inequality. Consumption smoothing cannot explain the differences between income and consumption at the very bottom, but the declining quality of income data can. Asset price changes likely account for some of the differences between the measures in recent years for the top half of the distribution.
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| Household Wealth Trends in the United States, 1962 to 2013: What Happened over the Great Recession? | Edward N. Wolff |
Household Wealth Trends in the United States, 1962 to 2013: What Happened over the Great Recession?Author: Edward N. WolffPublisher: RSF Date: 11/2016 I look at wealth trends from 1962 to 2013, particularly for the middle class. Asset prices plunged between 2007 and 2010 but then rebounded from 2010 to 2013. The most telling finding is that median wealth plummeted by 44 percent between 2007 and 2010, almost double the drop in housing prices. Wealth inequality, after almost two decades of little movement, was up sharply from 2007 to 2010. This sharp fall in median net worth and rise in overall wealth inequality are traceable primarily to the high leverage of middle-class families, the high share of homes in their portfolio, and the plunge in house prices. Rather remarkably, median (and mean) wealth did not essentially change from 2010 to 2013 despite the rebound in asset prices. The proximate cause was the high dissavings of the middle class. Wealth inequality also remained largely unchanged. |
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| Do Rising Top Incomes Lead to Increased Borrowing in the Rest of the Distribution? | Jeffrey Thompson |
Do Rising Top Incomes Lead to Increased Borrowing in the Rest of the Distribution?Author: Jeffrey ThompsonPublisher: Federal Reserve Board of Governors Date: 05/2016 One potential consequence of rising concentration of income at the top of the distribution isincreased borrowing, as less affluent households attempt to maintain standards of living with less income. This paper explores the “keeping up with the Joneses” phenomenon using data from the Survey of Consumer Finances. Specifically, it examines the responsiveness of payment-to-income ratios for different debt types at different parts of the income distribution to changes in the income thresholds at the 95th and 99th percentiles. The analysis provides some evidence indicating that household debt payments are responsive to rising top incomes. Middle and upper middle income households take on more housing-related debt and have higher housing debt payment to income ratios in places with higher top income levels. Among households at the bottom of the income distribution there is a decline in non-mortgage borrowing and debt payments in areas with rising top-income levels, consistent with restrictions in the supply of credit. The analysis also consistently shows that 95th percentile income has a greater influence on borrowing and debt payment across in the rest of the distribution than the more affluent 99th percentile level. |
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