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Earnings Through the Stages: Using Tax Data to Test for Sources of Error in CPS ASEC Earnings and Inequality Measures
September 2024
Working Paper Number:
CES-24-52
In this paper, I explore the impact of generalized coverage error, item non-response bias, and measurement error on measures of earnings and earnings inequality in the CPS ASEC. I match addresses selected for the CPS ASEC to administrative data from 1040 tax returns. I then compare earnings statistics in the tax data for wage and salary earnings in samples corresponding to seven stages of the CPS ASEC survey production process. I also compare the statistics using the actual survey responses. The statistics I examine include mean earnings, the Gini coefficient, percentile earnings shares, and shares of the survey weight for a range of percentiles. I examine how the accuracy of the statistics calculated using the survey data is affected by including imputed responses for both those who did not respond to the full CPS ASEC and those who did not respond to the earnings question. I find that generalized coverage error and item nonresponse bias are dominated by measurement error, and that an important aspect of measurement error is households reporting no wage and salary earnings in the CPS ASEC when there are such earnings in the tax data. I find that the CPS ASEC sample misses earnings at the high end of the distribution from the initial selection stage and that the final survey weights exacerbate this.
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Measuring Income of the Aged in Household Surveys: Evidence from Linked Administrative Records
June 2024
Working Paper Number:
CES-24-32
Research has shown that household survey estimates of retirement income (defined benefit pensions and defined contribution account withdrawals) suffer from substantial underreporting which biases downward measures of financial well-being among the aged. Using data from both the redesigned 2016 Current Population Survey Annual Social and Economic Supplement (CPS ASEC) and the Health and Retirement Study (HRS), each matched with administrative records, we examine to what extent underreporting of retirement income affects key statistics such as reliance on Social Security benefits and poverty among the aged. We find that underreporting of retirement income is still prevalent in the CPS ASEC. While the HRS does a better job than the CPS ASEC in terms of capturing retirement income, it still falls considerably short compared to administrative records. Consequently, the relative importance of Social Security income remains overstated in household surveys'53 percent of elderly beneficiaries in the CPS ASEC and 49 percent in the HRS rely on Social Security for the majority of their incomes compared to 42 percent in the linked administrative data. The poverty rate for those aged 65 and over is also overstated'8.8 percent in the CPS ASEC and 7.4 percent in the HRS compared to 6.4 percent in the linked administrative data. Our results illustrate the effects of using alternative data sources in producing key statistics from the Social Security Administration's Income of the Aged publication.
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Interpreting Cohort Profiles of Lifecycle Earnings Volatility
April 2024
Working Paper Number:
CES-24-21
We present new estimates of earnings volatility over time and the lifecycle for men and women by race and human capital. Using a long panel of restricted-access administrative Social Security earnings linked to the Current Population Survey, we estimate volatility with both transparent summary measures, as well as decompositions into permanent and transitory components. From the late 1970s to the mid 1990s there is a strong negative trend in earnings volatility for both men and women. We show this is driven by a reduction in transitory variance. Starting in the mid 1990s there is relative stability in trends of male earnings volatility because of an increase in the variance of permanent shocks, especially among workers without a college education, and a more attenuated trend decline among women. Cohort analyses indicate a strong U-shape pattern of volatility over the working life, which comes from large permanent shocks early and later in the lifecycle. However, this U-shape shifted downward and leftward in more recent cohorts, the latter from the fanning out of lifecycle transitory volatility in younger cohorts. These patterns are more pronounced among White men and women compared to Black workers.
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The Icing on the Cake: The Effects of Monetary Incentives on Income Data Quality in the SIPP
January 2024
Working Paper Number:
CES-24-03
Accurate measurement of key income variables plays a crucial role in economic research and policy decision-making. However, the presence of item nonresponse and measurement error in survey data can cause biased estimates. These biases can subsequently lead to sub-optimal policy decisions and inefficient allocation of resources. While there have been various studies documenting item nonresponse and measurement error in economic data, there have not been many studies investigating interventions that could reduce item nonresponse and measurement error. In our research, we investigate the impact of monetary incentives on reducing item nonresponse and measurement error for labor and investment income in the Survey of Income and Program Participation (SIPP). Our study utilizes a randomized incentive experiment in Waves 1 and 2 of the 2014 SIPP, which allows us to assess the effectiveness of incentives in reducing item nonresponse and measurement error. We find that households receiving incentives had item nonresponse rates that are 1.3 percentage points lower for earnings and 1.5 percentage points lower for Social Security income. Measurement error was 6.31 percentage points lower at the intensive margin for interest income, and 16.48 percentage points lower for dividend income compared to non-incentive recipient households. These findings provide valuable insights for data producers and users and highlight the importance of implementing strategies to improve data quality in economic research.
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Self-Employment Income Reporting on Surveys
April 2023
Working Paper Number:
CES-23-19
We examine the relation between administrative income data and survey reports for self-employed and wage-earning respondents from 2000 - 2015. The self-employed report 40 percent more wages and self-employment income in the survey than in tax administrative records; this estimate nets out differences between these two sources that are also shared by wage-earners. We provide evidence that differential reporting incentives are an important explanation of the larger self-employed gap by exploiting a well-known artifact ' self-employed respondents exhibit substantial bunching at the
first EITC kink in their administrative records. We do not observe the same behavior in their survey responses even after accounting for survey measurement concerns.
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National Experimental Wellbeing Statistics - Version 1
February 2023
Working Paper Number:
CES-23-04
This is the U.S. Census Bureau's first release of the National Experimental Wellbeing Statistics (NEWS) project. The NEWS project aims to produce the best possible estimates of income and poverty given all available survey and administrative data. We link survey, decennial census, administrative, and third-party data to address measurement error in income and poverty statistics. We estimate improved (pre-tax money) income and poverty statistics for 2018 by addressing several possible sources of bias documented in prior research. We address biases from 1) unit nonresponse through improved weights, 2) missing income information in both survey and administrative data through improved imputation, and 3) misreporting by combining or replacing survey responses with administrative information. Reducing survey error substantially affects key measures of well-being: We estimate median household income is 6.3 percent higher than in survey estimates, and poverty is 1.1 percentage points lower. These changes are driven by subpopulations for which survey error is particularly relevant. For house holders aged 65 and over, median household income is 27.3 percent higher and poverty is 3.3 percentage points lower than in survey estimates. We do not find a significant impact on median household income for householders under 65 or on child poverty. Finally, we discuss plans for future releases: addressing other potential sources of bias, releasing additional years of statistics, extending the income concepts measured, and including smaller geographies such as state and county.
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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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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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Immigrants' Earnings Growth and Return Migration from the U.S.: Examining their Determinants using Linked Survey and Administrative Data
March 2019
Working Paper Number:
CES-19-10
Using a novel panel data set of recent immigrants to the U.S. (2005-2007) from individual-level linked U.S. Census Bureau survey data and Internal Revenue Service (IRS) administrative records, we identify the determinants of return migration and earnings growth for this immigrant arrival cohort. We show that by 10 years after arrival almost 40 percent have return migrated. Our analysis examines these flows by educational attainment, country of birth, and English language ability separately for each gender. We show, for the first time, that return migrants experience downward earnings mobility over two to three years prior to their return migration. This finding suggests that economic shocks are closely related to emigration decisions; time-variant unobserved characteristics may be more important in determining out-migration than previously known. We also show that wage assimilation with native-born populations occurs fairly quickly; after 10 years there is strong convergence in earnings by several characteristics. Finally, we confirm that the use of stock-based panel data lead to estimates of slower earnings growth than is found using repeated cross-section data. However, we also show, using selection-correction methods in our panel data, that stock-based panel data may understate the rate of earnings growth for the initial immigrant arrival cohort when emigration is not accounted for.
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The Distributional Effects of Minimum Wages: Evidence from Linked Survey and Administrative Data
March 2018
Working Paper Number:
carra-2018-02
States and localities are increasingly experimenting with higher minimum wages in response to rising income inequality and stagnant economic mobility, but commonly used public datasets offer limited opportunities to evaluate the extent to which such changes affect earnings growth. We use administrative earnings data from the Social Security Administration linked to the Current Population Survey to overcome important limitations of public data and estimate effects of the minimum wage on growth incidence curves and income mobility profiles, providing insight into how cross-sectional effects of the minimum wage on earnings persist over time. Under both approaches, we find that raising the minimum wage increases earnings growth at the bottom of the distribution, and those effects persist and indeed grow in magnitude over several years. This finding is robust to a variety of specifications, including alternatives commonly used in the literature on employment effects of the minimum wage. Instrumental variables and subsample analyses indicate that geographic mobility likely contributes to the effects we identify. Extrapolating from our estimates suggests that a minimum wage increase comparable in magnitude to the increase experienced in Seattle between 2013 and 2016 would have blunted some, but not nearly all, of the worst income losses suffered at the bottom of the income distribution during the Great Recession.
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