Using administrative records to assess earnings reporting error in the survey of income and program participation

Pedace, Roberto; Bates, Nancy

doi:10.3233/jem-2000-0180

Cited by 51 publications

(32 citation statements)

References 12 publications

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“…SIPP log earnings are 4.8 percent lower than administrative earnings. These results are consistent with previous findings, which show survey earnings to be modestly lower than administrative earnings, but largely not biased in estimating true earnings (Akee 2011;Bound and Krueger 1991;Pedace and Bates 2000).…”

Section: Analytical Strategysupporting

confidence: 95%

“…With regard to the occupation and industry dummies, 7 the coefficient for Accommodation/Food industry is consistent with Pedace and Bates' (2000) speculation. That is, workers in this sector tend to overreport excessively.…”

Section: Variance Component Of Measurement Error: Quantile Regressionsupporting

confidence: 73%

“…More problematic, the estimated effects of education at other points of earnings distribution (i.e., not at mean or median) could be biased. Pedace and Bates (2000) provide empirical support for the notion that studying the mean effects of response errors may not be sufficient. Using a SIPP 1992 file matched to SSA's Summary Earnings Records, the authors employ logit models to assess the probability of reporting 25 percent below or above true earnings.…”

Section: Covariates Of Measurement Error In Earningsmentioning

confidence: 82%

“…For example, workers in technical/sales had a higher likelihood to underreport their earnings. The magnitude of misreporting, Pedace and Bates (2000) find, is largest among the lowest earnings group. The authors speculate that significant overreporting at the bottom tenth of earnings distribution could be caused by the tendency of low earners to work in unstable labor markets or in service sectors receiving tips.…”

Section: Covariates Of Measurement Error In Earningsmentioning

confidence: 87%

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Response Error in Earnings

Kim

Tamborini

2012

Sociological Methods & Research

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This article examines the problem of response error in survey earnings data. Comparing workers' earnings reports in the U.S. Census Bureau's Survey of Income and Program Participation (SIPP) to their detailed W-2 earnings records from the Social Security Administration, we employ ordinary least squares (OLS) and quantile regression models to assess the effects of earnings determinants and demographic variables on measurement errors in 2004 SIPP earnings in terms of bias and variance. Results show that measurement errors in earnings are not classical, but mean-reverting. The directions of bias for subpopulations are not constant, but varying across levels of earnings. Highly educated workers more correctly report their earnings than less educated workers at higher earnings levels, but they tend to overreport at lower earnings levels. Black workers with high earnings underreport to a Downloaded from greater degree than comparable whites, while black workers with low earnings overreport to a greater degree. Some subpopulations exhibit higher variances of measurement errors than others. Blacks, Hispanics, high school dropouts, part-year employed workers, and occupation ''switchers'' tend to misreport-both over-and underreport-their earnings rather than unilaterally in one direction. The implications of our findings are discussed.

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Section: Analytical Strategysupporting

confidence: 95%

Section: Variance Component Of Measurement Error: Quantile Regressionsupporting

confidence: 73%

Section: Covariates Of Measurement Error In Earningsmentioning

confidence: 82%

Section: Covariates Of Measurement Error In Earningsmentioning

confidence: 87%

See 2 more Smart Citations

Response Error in Earnings

Kim

Tamborini

2012

Sociological Methods & Research

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“…Toward the final waves, around 35-40% of eligible households have fallen out of the survey. Third, because SSA earnings data come from respondents' tax records sent by employers, they contain little measurement error relative to survey-reported earnings, which are subject to misreporting (Pedace and Bates 2000).…”

Section: Matched Administrative Earnings Datamentioning

confidence: 99%