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Estimating Measurement Error in Annual Job Earnings: A Comparison of Survey and Administrative Data

Author

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  • John M. Abowd

    (Cornell University, Census Bureau NBER, CREST/INSEE, and IZA)

  • Martha H. Stinson

    (U.S. Census Bureau)

Abstract

We propose a new methodology that does not assume a prior specification of the statistical properties of the measurement errors and treats all sources as noisy measures of some underlying true value. The unobservable true value can be represented as a weighted average of all available measures, using weights that must be specified a priori unless there has been a truth audit. The Census Bureau's Survey of Income and Program Participation (SIPP) survey jobs are linked to Social Security Administration earnings data, creating two potential annual earnings observations. The reliability statistics for both sources are quite similar except for cases where the SIPP used imputations for some missing monthly earnings reports. © 2013 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • John M. Abowd & Martha H. Stinson, 2013. "Estimating Measurement Error in Annual Job Earnings: A Comparison of Survey and Administrative Data," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1451-1467, December.
  • Handle: RePEc:tpr:restat:v:95:y:2013:i:5:p:1451-1467
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    References listed on IDEAS

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    1. DeShazo, J. R., 2002. "Designing Transactions without Framing Effects in Iterative Question Formats," Journal of Environmental Economics and Management, Elsevier, vol. 43(3), pages 360-385, May.
    2. Kanninen Barbara J., 1995. "Bias in Discrete Response Contingent Valuation," Journal of Environmental Economics and Management, Elsevier, vol. 28(1), pages 114-125, January.
    3. Cooper Joseph C., 1993. "Optimal Bid Selection for Dichotomous Choice Contingent Valuation Surveys," Journal of Environmental Economics and Management, Elsevier, vol. 24(1), pages 25-40, January.
    4. Gallant, A. Ronald, 1982. "Unbiased determination of production technologies," Journal of Econometrics, Elsevier, vol. 20(2), pages 285-323, November.
    5. Herriges, Joseph A. & Shogren, Jason F., 1996. "Starting Point Bias in Dichotomous Choice Valuation with Follow-Up Questioning," Journal of Environmental Economics and Management, Elsevier, vol. 30(1), pages 112-131, January.
    6. Deacon, Robert T & Shapiro, Perry, 1975. "Private Preference for Collective Goods Revealed Through Voting on Referenda," American Economic Review, American Economic Association, pages 943-955.
    7. Trudy Ann Cameron & John Quiggin, 1992. "Estimation Using Contingent Valuation Data From a "Dichotomous Choice with Follow-Up" Questionnaire," UCLA Economics Working Papers 653, UCLA Department of Economics.
    8. Chen, Heng Z. & Randall, Alan, 1997. "Semi-nonparametric estimation of binary response models with an application to natural resource valuation," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 323-340.
    9. Carson, R.T. & Mitchell, R.C. & Hanemann, W.M. & Kopp, R.J. & Presser, S. & Ruud, P.A., 1992. "A Contingent Valuation Study of Lost Passive Use Values Resulting From the Exxon Valdez Oil Spill," MPRA Paper 6984, University Library of Munich, Germany.
    10. Creel, Michael & Loomis, John, 1997. "Semi-nonparametric Distribution-Free Dichotomous Choice Contingent Valuation," Journal of Environmental Economics and Management, Elsevier, pages 341-358.
    11. Cameron Trudy Ann & Quiggin John, 1994. "Estimation Using Contingent Valuation Data from a Dichotomous Choice with Follow-Up Questionnaire," Journal of Environmental Economics and Management, Elsevier, vol. 27(3), pages 218-234, November.
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    Citations

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    Cited by:

    1. Bruce D. Meyer & Nikolas Mittag, 2015. "Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net," Upjohn Working Papers and Journal Articles 15-242, W.E. Upjohn Institute for Employment Research.
    2. Andrew S. Green, 2017. "Hours Off the Clock," Working Papers 17-44, Center for Economic Studies, U.S. Census Bureau.
    3. repec:eee:ecolet:v:155:y:2017:i:c:p:19-23 is not listed on IDEAS
    4. Meyer, Bruce D. & Mittag, Nikolas, 2017. "Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net," IZA Discussion Papers 10943, Institute for the Study of Labor (IZA).
    5. Paulus, Alari, 2015. "Tax evasion and measurement error: An econometric analysis of survey data linked with tax records," ISER Working Paper Series 2015-10, Institute for Social and Economic Research.
    6. Whitaker, Stephan, 2015. "Big Data versus a Survey," Working Paper 1440, Federal Reserve Bank of Cleveland.
    7. Mittag, Nikolas, 2016. "Correcting for Misreporting of Government Benefits," IZA Discussion Papers 10266, Institute for the Study of Labor (IZA).
    8. Markus Jäntti & Stephen P. Jenkins, 2013. "Income Mobility," SOEPpapers on Multidisciplinary Panel Data Research 607, DIW Berlin, The German Socio-Economic Panel (SOEP).
    9. Dean Hyslop & Wilbur Townsend, 2016. "Earnings Dynamics and Measurement Error in Matched Survey and Administrative Data," Working Papers 16_18, Motu Economic and Public Policy Research.
    10. Dieter Vandelannoote & André Decoster & Toon Vanheukelom & Gerlinde Verbist, 2016. "Evaluating The Quality Of Gross Incomes In SILC: Compare Them With Fiscal Data And Re-calibrate Them Using EUROMOD," International Journal of Microsimulation, International Microsimulation Association, vol. 9(3), pages 5-34.
    11. Hyslop, Dean R. & Townsend, Wilbur, 2017. "Employment misclassification in survey and administrative reports," Economics Letters, Elsevier, vol. 155(C), pages 19-23.
    12. van Bergeijk, P.A.G., 2017. "Measurement error of global production," ISS Working Papers - General Series 632, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
    13. Bruce D. Meyer & Wallace K. C. Mok & James X. Sullivan, 2015. "Household Surveys in Crisis," Journal of Economic Perspectives, American Economic Association, pages 199-226.
    14. Bruce Meyer & Nikolas Mittag, 2017. "Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net," Working Papers 2017-075, Human Capital and Economic Opportunity Working Group.
    15. Bruce D. Meyer & Wallace K. C. Mok & James X. Sullivan, 2015. "Household Surveys in Crisis," Journal of Economic Perspectives, American Economic Association, pages 199-226.

    More about this item

    Keywords

    measurement error; earnings; matched survey-administrative data; linear mixed-effects model;

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs

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