The March Current Population Survey (CPS) and the Survey of Income and Program
Participation (SIPP) produce different aggregates and distributions of annual wages. An excess of
high wages and shortage of low wages occurs in the March CPS. SIPP shows the opposite, an
excess of low wages and shortage of high wages. Exactly-matched Detailed Earnings Records
(DER) from the Social Security Administration allow comparing March CPS and SIPP people's
wages using data independent of the surveys. Findings include the following. March CPS and
SIPP people differ little in their true wage characteristics. March CPS and SIPP represent a
worker's percentile rank better than the dollar amount of wages. Workers with one job and low
work effort have underestimated March CPS wages. March CPS has a higher level of
"underground" wages than SIPP, and increasingly so in the 1990s. March CPS has a higher level
of self-employment income "misclassified" as wages than SIPP, and increasingly so in the 1990s.
These trends may explain one-third of March CPS's 6-percentage-point increase in aggregate
wages relative to independent estimates from 1993 to 1995. Finally, the paper delineates March
CPS occupations disproportionately likely to be absent from the administrative data entirely or to
"misclassify" self-employment income as wages.
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Further Evidence from Census 2000 About Earnings by Detailed Occupation for Men and Women: The Role of Race and Hispanic Origin
November 2011
Working Paper Number:
CES-11-37
A 2004 report by the author reviewed data from Census 2000 and concluded "There is a substantial gap in median earnings between men and women that is unexplained, even after controlling for work experience (to the extent it can be represented by age and presence of children), education, and occupation." This paper extends the analysis and concludes that once those characteristics are controlled for, no further explanatory power is attributable to race or Hispanic origin.
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Occupation Inflation in the Current Population Survey
September 2012
Working Paper Number:
CES-12-26
A common caveat often accompanying results relying on household surveys regards respondent error. There is research using independent, presumably error-free administrative data, to estimate the extent of error in the data, the correlates of error, and potential corrections for the error. We investigate measurement error in occupation in the Current Population Survey (CPS) using the panel component of the CPS to identify those that incorrectly report changing occupation. We find evidence that individuals are inflating their occupation to higher skilled and higher paying occupations than the ones they actually perform. Occupation inflation biases the education and race coefficients in standard Mincer equation results within occupations.
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Social, Economic, Spatial, and Commuting Patterns of Self-Employed Jobholders
April 2007
Working Paper Number:
tp-2007-03
A significant number of employees within the United States identify themselves as selfemployed,
and they are distinct from the larger group identified as private jobholders. While
socioeconomic and spatial information on these individuals is readily available in standard
datasets, such as the 2000 Decennial Census Long Form, it is possible to gain further information
on their wage earnings by using data from administrative wage records. This study takes
advantage of firm-based data from Unemployment Insurance administrative wage records linked
with the Census Bureau's household-based data in order to examine self-employed jobholders -
both as a whole and as subgroups defined according to their earned wage status - by their
demographic characteristics as well as their economic, commuting, and spatial location
outcomes. Additionally, this report evaluates whether self-employed jobholders and the defined
subgroups should be included explicitly in future labor-workforce analyses and transportation
modeling. The analyses in this report use the sample of self-employed workers who lived in Los
Angeles County, California.
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An Analysis of Sample Selection and the Reliability of Using Short-term Earnings Averages in SIPP-SSA Matched Data
December 2011
Working Paper Number:
CES-11-39
In this paper, we document the extent to which the sample of the Survey of Income and Program Participation that is matched to the Social Security Administration's administrative earnings records is nationally representative. We conclude that the match bias is small, so selection is not a serious concern. The matched sample over-represents individuals who are wealthy, who have financial assets or who have received a government-transfer and under-represents individuals who attrited from the SIPP. We use this matched sample to examine the relationship between short-term averages of earnings from the SIPP earnings and average lifetime earnings from the administrative records. Our estimates suggest that using short averages of earnings may understate the effects of permanent income on particular outcomes of interest.
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Social, Economic, Spatial, and Commuting Patterns of Informal Jobholders
April 2007
Working Paper Number:
tp-2007-02
A significant number of employees within the United States can be considered "informal" or
"off-the-books" workers. These workers, who by definition do not appear in administrative wage
records, are distinct from the larger group of private jobholders who do appear in administrative
records. However, while socioeconomic and spatial information on these individuals is readily
available in standard datasets, such as the 2000 Decennial Census Long Form, it is not possible
to identify the informal workers by only using such data because of the lack of accurate, formal
wage records. This study takes advantage of firm-based data that originates in Unemployment
Insurance administrative wage records linked with the Census Bureau's household-based data in
order to examine informal jobholders by their demographic characteristics as well as their
economic, commuting, and spatial location outcomes. In addition this report evaluates whether
informal jobholders should be included explicitly in future labor-workforce analyses and
transportation modeling. The analyses in this report use the sample of workers who lived in Los
Angeles County, California.
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Exploring Differences in Employment between Household and Establishment Data
April 2009
Working Paper Number:
CES-09-09
Using a large data set that links individual Current Population Survey (CPS) records to employer-reported administrative data, we document substantial discrepancies in basic measures of employment status that persist even after controlling for known definitional differences between the two data sources. We hypothesize that reporting discrepancies should be most prevalent for marginal workers and marginal jobs, and find systematic associations between the incidence of reporting discrepancies and observable person and job characteristics that are consistent with this hypothesis. The paper discusses the implications of the reported findings for both micro and macro labor market analysis
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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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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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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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Long-Run Earnings Volatility and Health Insurance Coverage: Evidence from the SIPP Gold Standard File
October 2011
Working Paper Number:
CES-11-35
Despite the notable increase in earnings volatility and the attention paid to the growing ranks of the uninsured, the relationship between career earnings and short- and mediumrun health insurance status has been ignored due to a lack of data. I use a new dataset, the SIPP Gold Standard File, that merges health insurance status and demographics from the Survey of Income and Program Participation with career earnings records from the Social Security Administration (SSA) and the Internal Revenue Service (IRS) to examine the relationship between long-run family earnings volatility and health insurance coverage. I find that more volatile career earnings are associated with an increased probability of experiencing an uninsured episode, with larger effects for men, young workers, and the unmarried. These findings are consistent with the 'scarring' literature, and suggest the importance of safety-net measures for job losses and health insurance coverage.
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