No: it is at least as large at bottom percentiles of the earnings distribution. Conditional quantile regressions reveal that while the gap at top percentiles is largest among the most-educated, the gap at bottom percentiles is largest among the least-educated. Gender differences in labor supply create more pay inequality among the least-educated than they do among the most-educated. The pay gap has declined throughout the distribution since 2006, but it declined more for the most-educated women. Current economics-of-gender research focuses heavily on the top end; equal emphasis should be placed on mechanisms driving gender inequality for noncollege-educated workers.
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The Gender Pay Gap and Its Determinants Across the Human Capital Distribution
June 2023
Working Paper Number:
CES-23-31R
This paper links American Community Survey data and postsecondary transcript records to examine how the gender pay gap varies across the distribution of education credentials for a sample of 2003-2013 graduates. Although recent literature emphasizes gender inequality among the most-educated, we find a smaller gender pay gap at higher education levels. Field-of-degree and occupation effects explain most of the gap among top bachelor's graduates, while work hours and unobserved channels matter more for less-competitive bachelor's, associate, and certificate graduates. We develop a novel decomposition of the child penalty to examine the role of children in explaining these results.
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Using Internal Current Population Survey Data to Reevaluate Trends in Labor Earnings Gaps by Gender, Race, and Education Level
July 2008
Working Paper Number:
CES-08-18
Most empirical studies of trends in labor earnings gaps by gender, race or education level are based on data from the public use March Current Population Survey (CPS). Using the internal March CPS, we show that inconsistent topcoding in the public use data will understate these gaps and inaccurately capture their trends. We create a cell mean series beginning in 1975 that provides the mean of all values above the topcode for each income source in the public use March CPS and better approximate earnings gaps found in the internal March CPS than was previously possible using publically available data.
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Selection and Specialization in the Evolution of Marriage Earnings Gaps
October 2015
Working Paper Number:
CES-15-36
We examine changes in marriage and earnings patterns across four cohorts born between 1936 and 1975, using data from a series of Survey of Income and Program Participation panels linked to administrative data on earnings. We find that for both men and women, marriage has become increasingly positively associated with education and earnings potential. We compare ordinary least squares (OLS) and fixed effect (FE) estimates of the earnings differential associated with marriage. We find that the marriage earnings gap fell for women in fixed-effect estimates implying that the impact of specialization has diminished over time. We also find that increasingly positive selection into marriage means that OLS estimates overstate the reduction in the marriage earnings gap. While our findings imply that marriage is no longer associated with lower earnings among women without minor children in our most recent cohort, the motherhood gap remains large. Among men, we find that the marriage premium actually increases for more recent birth cohorts in fixed-effects regressions.
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Understanding Earnings Instability: How Important are Employment Fluctuations and Job Changes?
August 2009
Working Paper Number:
CES-09-20
Using three panel datasets (the matched CPS, the SIPP, and the newly available Longitudinal Employment and Household Dynamics (LEHD) data), we examine trends in male earnings instability in recent decades. In contrast to several papers that find a recent upward trend in earnings instability using the PSID data, we find that earnings instability has been remarkably stable in the 1990s and the 2000s. We find that job changing rates remained relatively constant casting doubt on the importance of labor market 'churning.' We find some evidence that earnings instability increased among job stayers which lends credence to the view that greater reliance on incentive pay increased instability of worker pay. We also find an offsetting decrease in earnings instability among job changers due largely to declining unemployment associated with job changes. One caveat to our findings is that we focus on men who have positive earnings in two adjacent years and thus ignore men who exit the labor force or re-enter after an extended period. Preliminary investigation suggests that ignoring these transitions understates the rise in earnings instability over the past two decades.
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Trends in Earnings Volatility using Linked Administrative and Survey Data
August 2020
Working Paper Number:
CES-20-24
We document trends in earnings volatility separately by gender in combination with other characteristics such as race, educational attainment, and employment status using unique linked survey and administrative data for the tax years spanning 1995-2015. We also decompose the variance of trend volatility into within- and between-group contributions, as well as transitory and permanent shocks. Our results for continuously working men suggest that trend earnings volatility was stable over our period in both survey and tax data, though with a substantial countercyclical business-cycle component. Trend earnings volatility among women declined over the period in both survey and administrative data, but unlike for men, there was no change over the Great Recession. The variance decompositions indicate that nonresponders, low-educated, racial minorities, and part-year workers have the greatest group specific earnings volatility, but with the exception of part-year workers, they contribute least to the level and trend of volatility owing to their small share of the population. There is evidence of stable transitory volatility, but rising permanent volatility over the past two decades in male and female earnings.
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Trends in the Relative Household Income of Working-Age Men with Work Limitations: Correcting the Record Using Internal Current Population Survey Data
March 2008
Working Paper Number:
CES-08-05
Previous research measuring the economic well-being of working-age men with work limitations relative to such men without work limitations in the public use March Current Population Survey (CPS) systematically understates the mean household income of both groups; overstates the relative household income of those with work limitations; and understates the decline in their relative household income over time. Using the internal March CPS, we demonstrate this by creating a cell mean series beginning in 1975 that provides the mean reported income of all topcoded persons for each source of income in the public use March CPS data. Using our cell mean series with the public use March CPS, we closely match the yearly mean income of working-age men with and without work limitations over the period 1987-2004 in the internal data and show that this match is superior to ones using alternative methods of correcting for topcoding currently used in the disability literature. We then provide levels and trends in the relative income of working-age men with work limitations from 1980-2006, the earliest year in the March CPS that such comparisons can be made.
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An Evaluation of the Gender Wage Gap Using Linked Survey and Administrative Data
November 2020
Working Paper Number:
CES-20-34
The narrowing of the gender wage gap has slowed in recent decades. However, current estimates show that, among full-time year-round workers, women earn approximately 18 to 20 percent less than men at the median. Women's human capital and labor force characteristics that drive wages increasingly resemble men's, so remaining differences in these characteristics explain less of the gender wage gap now than in the past. As these factors wane in importance, studies show that others like occupational and industrial segregation explain larger portions of the gender wage gap. However, a major limitation of these studies is that the large datasets required to analyze occupation and industry effectively lack measures of labor force experience. This study combines survey and administrative data to analyze and improve estimates of the gender wage gap within detailed occupations, while also accounting for gender differences in work experience. We find a gender wage gap of 18 percent among full-time, year-round workers across 316 detailed occupation categories. We show the wage gap varies significantly by occupation: while wages are at parity in some occupations, gaps are as large as 45 percent in others. More competitive and hazardous occupations, occupations that reward longer hours of work, and those that have a larger proportion of women workers have larger gender wage gaps. The models explain less of the wage gap in occupations with these attributes. Occupational characteristics shape the conditions under which men and women work and we show these characteristics can make for environments that are more or less conducive to gender parity in earnings.
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Using the P90/P10 Index to Measure U.S. Inequality Trends with Current Population Survey Data: A View From Inside the Census Bureau Vaults
June 2007
Working Paper Number:
CES-07-17
The March Current Population Survey (CPS) is the primary data source for estimation of levels and trends in labor earnings and income inequality in the USA. Time-inconsistency problems related to top coding in theses data have led many researchers to use the ratio of the 90th and 10th percentiles of these distributions (P90/P10) rather than a more traditional summary measure of inequality. With access to public use and restricted-access internal CPS data, and bounding methods, we show that using P90/P10 does not completely obviate time inconsistency problems, especially for household income inequality trends. Using internal data, we create consistent cell mean values for all top-coded public use values that, when used with public use data, closely track inequality trends in labor earnings and household income using internal data. But estimates of longer-term inequality trends with these corrected data based on P90/P10 differ from those based on the Gini coefficient. The choice of inequality measure matters.
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Gifted Identification Across the Distribution of Family Income
December 2025
Authors:
Quentin Brummet,
Andrew Penner,
Emily Penner,
Leah R. Clark,
Michelle Spiegel,
Paul Hanselman,
Nicholas J. Ainsworth,
Aaron J. Ainsworth,
Christopher Cleveland,
Jacob Hibel,
Andrew Saultz
Working Paper Number:
CES-25-73
Currently, 6.1 percent of K-12 students in the United States receive gifted education. Using education and IRS data that provide information on students and their family income, we show pronounced differences in who schools identify as gifted across the distribution of family income. Under 4 percent of students in the lowest income percentile are identified as gifted, compared with 20 percent of those in the top income percentile. Income-based differences persist after accounting for student test scores and exist across students of different sexes and racial/ethnic groups, underscoring the importance of family resources for gifted identification in schools.
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Black-White Differences in Intergenerational Economic Mobility in the U.S.
December 2011
Working Paper Number:
CES-11-40
Traditional measures of intergenerational mobility such as the intergenerational elasticity are not useful for inferences concerning group differences in mobility with respect to the pooled income distribution. This paper uses transition probabilities and measures of 'directional rank mobility' that can identify inter-racial differences in intergenerational mobility. The study uses two data sources including one that contains social security earnings for a large intergenerational sample. I find that recent cohorts of blacks are not only significantly less upwardly mobile but also significantly more downwardly mobile than whites. This implies a steady-state distribution in which there is no racial convergence in income. A descriptive analysis using covariates reveals that test scores in adolescence can explain much of the racial difference in both upward and downward mobility. Family structure can account for some of the racial gap in upward mobility but not downward mobility. Completed schooling and parental wealth also appear to account for some of the racial gaps in intergenerational mobility.
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