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Estimating Measurement Error in SIPP Annual Job Earnings: A Comparison of Census Bureau Survey and SSA Administrative Data

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  • John Abowd
  • Martha Stinson

Abstract

We quantify sources of variation in annual job earnings data collected by the Survey of Income and Program Participation (SIPP) to determine how much of the variation is the result of measurement error. Jobs reported in the SIPP are linked to jobs reported in an administrative database, the Detailed Earnings Records (DER) drawn from the Social Security Administration�s Master Earnings File, a universe file of all earnings reported on W-2 tax forms. As a result of the match, each job potentially has two earnings observations per year: survey and administrative. Unlike previous validation studies, both of these earnings measures are viewed as noisy measures of some underlying true amount of annual earnings. While the existence of survey error resulting from respondent mistakes or misinterpretation is widely accepted, the idea that administrative data are also error-prone is new. Possible sources of employer reporting error, employee under-reporting of compensation such as tips, and general differences between how earnings may be reported on tax forms and in surveys, necessitates the discarding of the assumption that administrative data are a true measure of the quantity that the survey was designed to collect. In addition, errors in matching SIPP and DER jobs, a necessary task in any use of administrative data, also contribute to measurement error in both earnings variables. We begin by comparing SIPP and DER earnings for different demographic and education groups of SIPP respondents. We also calculate different measures of changes in earnings for individuals switching jobs. We estimate a standard earnings equation model using SIPP and DER earnings and compare the resulting coefficients. Finally exploiting the presence of individuals with multiple jobs and shared employers over time, we estimate an econometric model that includes random person and firm effects, a common error component shared by SIPP and DER earnings, and two independent error components that represent the variation unique to each earnings measure. We compare the variance components from this model and consider how the DER and SIPP differ across unobservable components.

Suggested Citation

  • John Abowd & Martha Stinson, 2011. "Estimating Measurement Error in SIPP Annual Job Earnings: A Comparison of Census Bureau Survey and SSA Administrative Data," Working Papers 11-20, Center for Economic Studies, U.S. Census Bureau.
  • Handle: RePEc:cen:wpaper:11-20
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    References listed on IDEAS

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    Cited by:

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    2. Babette Bühler & Katja Möhring & Andreas P. Weiland, 2022. "Assessing dissimilarity of employment history information from survey and administrative data using sequence analysis techniques," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4747-4774, December.
    3. Hamish Low & Costas Meghir & Luigi Pistaferri, 2010. "Wage Risk and Employment Risk over the Life Cycle," American Economic Review, American Economic Association, vol. 100(4), pages 1432-1467, September.
    4. Wojciech Kopczuk & Emmanuel Saez & Jae Song, 2007. "Uncovering the American Dream: Inequality and Mobility in Social Security Earnings Data since 1937," NBER Working Papers 13345, National Bureau of Economic Research, Inc.
    5. Celik Sule & Juhn Chinhui & McCue Kristin & Thompson Jesse, 2012. "Recent Trends in Earnings Volatility: Evidence from Survey and Administrative Data," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 12(2), pages 1-26, June.
    6. Jung, Juergen & Hall, Diane M. Harnek & Rhoads, Thomas, 2013. "Does the availability of parental health insurance affect the college enrollment decision of young Americans?," Economics of Education Review, Elsevier, vol. 32(C), pages 49-65.
    7. John L. Czajka & Gabrielle Denmead, "undated". "Income Measurement for the 21st Century: Updating the Current Population Survey," Mathematica Policy Research Reports a34dabaf1455421f87c797202, Mathematica Policy Research.
    8. German Cubas & Pedro Silos, 2017. "Career Choice and the Risk Premium in the Labor Market," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 26, pages 1-18, October.
    9. Liu, Kai, 2015. "Wage Risk and the Value of Job Mobility in Early Employment Careers," IZA Discussion Papers 9256, Institute of Labor Economics (IZA).
    10. Katharine G. Abraham & John Haltiwanger & Kristin Sandusky & James R. Spletzer, 2013. "Exploring Differences in Employment between Household and Establishment Data," Journal of Labor Economics, University of Chicago Press, vol. 31(S1), pages 129-172.
    11. Nikolas Mittag, 2013. "A Method Of Correcting For Misreporting Applied To The Food Stamp Program," Working Papers 13-28, Center for Economic Studies, U.S. Census Bureau.
    12. Bowlus, Audra J. & Liu, Huju, 2013. "The contributions of search and human capital to earnings growth over the life cycle," European Economic Review, Elsevier, vol. 64(C), pages 305-331.
    13. Jeffrey A. Groen, 2011. "Seasonal Differences in Employment between Survey and Administrative Data," Working Papers 443, U.S. Bureau of Labor Statistics.
    14. Akee, Randall, 2011. "Errors in self-reported earnings: The role of previous earnings volatility and individual characteristics," Journal of Development Economics, Elsevier, vol. 96(2), pages 409-421, November.
    15. Lisa M. Dragoset & Gary S. Fields, 2006. "U.S. Earnings Mobility: Comparing Survey-Based and Administrative-Based Estimates," Working Papers 55, ECINEQ, Society for the Study of Economic Inequality.
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    17. Chatterji, Pinka & Brandon, Peter & Markowitz, Sara, 2016. "Job mobility among parents of children with chronic health conditions: Early effects of the 2010 Affordable Care Act," Journal of Health Economics, Elsevier, vol. 48(C), pages 26-43.

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