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Match Bias from Earnings Imputation in the Current Population Survey: The Case of Imperfect Matching

  • Bollinger, Christopher R.

    ()

    (University of Kentucky)

  • Hirsch, Barry

    ()

    (Georgia State University)

This paper examines alternative forms of match bias arising from earnings imputation. Wage equation parameters are estimated based on mixed samples of workers who do and do not report earnings, the latter group being assigned earnings of donors who share some but not all the attributes of the recipients. Regressions that include attributes not used as imputation match criteria (e.g., union status) are severely biased. Related forms of match bias arise with respect to attributes used as match criteria, but matched imperfectly. For example, an imperfect match on schooling creates bias that flattens estimated earnings profiles within low, middle, and high education groups, while creating large jumps in returns across groups. The same pattern arises in wage-age profiles. The paper provides a general analytic expression to correct match bias in regression coefficients under the assumption of conditional mean missing at random. The full sample correction approach is compared to the alternative of omitting imputed earners from the sample, with and without reweighting. Additional problems considered are bias in longitudinal analysis and the presence of dated donors.

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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 1846.

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Length: 47 pages
Date of creation: Nov 2005
Date of revision:
Publication status: published in: Journal of Labor Economics, 2006, 24 (3), 483-519
Handle: RePEc:iza:izadps:dp1846
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  1. Willis, Robert J., 1987. "Wage determinants: A survey and reinterpretation of human capital earnings functions," Handbook of Labor Economics, in: O. Ashenfelter & R. Layard (ed.), Handbook of Labor Economics, edition 1, volume 1, chapter 10, pages 525-602 Elsevier.
  2. Barry T. Hirsch, 2005. "Why do part-time workers earn less? The role of worker and job skills," Industrial and Labor Relations Review, ILR Review, Cornell University, ILR School, vol. 58(4), pages 525-551, July.
  3. Horowitz, J.L. & Manski, C.F., 1995. "Censoring of Outcomes and Regressors Due to Survey Nonresponse: Identification and Estimation Using Weights and Imputations," Working papers 9525, Wisconsin Madison - Social Systems.
  4. Marco Manacorda, 2004. "Can the Scala Mobile Explain the Fall and Rise of Earnings Inequality in Italy? A Semiparametric Analysis, 19771993," Journal of Labor Economics, University of Chicago Press, vol. 22(3), pages 585-614, July.
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  6. Murphy, Kevin M & Welch, Finis, 1990. "Empirical Age-Earnings Profiles," Journal of Labor Economics, University of Chicago Press, vol. 8(2), pages 202-29, April.
  7. Richard B. Freeman, 1983. "Longitudinal Analyses of the Effects of Trade Unions," NBER Working Papers 1207, National Bureau of Economic Research, Inc.
  8. Melissa Clark & David Jaeger, 2006. "Natives, the foreign-born and high school equivalents: new evidence on the returns to the GED," Journal of Population Economics, Springer, vol. 19(4), pages 769-793, October.
  9. Aigner, Dennis J., 1973. "Regression with a binary independent variable subject to errors of observation," Journal of Econometrics, Elsevier, vol. 1(1), pages 49-59, March.
  10. Card, David, 1996. "The Effect of Unions on the Structure of Wages: A Longitudinal Analysis," Econometrica, Econometric Society, vol. 64(4), pages 957-79, July.
  11. Horowitz, Joel & Manski, Charles, 1997. "Nonparametric Analysis of Randomized Experiments With Missing Covariate and Outcome Data," Working Papers 97-16, University of Iowa, Department of Economics.
  12. Bollinger, Christopher R., 1996. "Bounding mean regressions when a binary regressor is mismeasured," Journal of Econometrics, Elsevier, vol. 73(2), pages 387-399, August.
  13. Lee Lillard & James P. Smith & Finis Welch, 2004. "What Do We Really Know About Wages: The Importance of Nonreporting and Census Imputation," Labor and Demography 0404005, EconWPA.
  14. Barry T. Hirsch, 2005. "Why Do Part-Time Workers Earn Less? The Role of Worker and Job Skills," ILR Review, Cornell University, ILR School, vol. 58(4), pages 525-551, July.
  15. Hirsch, Barry & Schumacher, Edward J., 2003. "Match Bias in Wage Gap Estimates Due to Earnings Imputation," IZA Discussion Papers 783, Institute for the Study of Labor (IZA).
  16. Molinari, Francesca, 2010. "Missing Treatments," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 82-95.
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