Response Error in Earnings

Abstract

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 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.