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Work experience as a source of specification error in earnings models: implications for gender wage decompositions

  • Tracy Regan

    ()

  • Ronald Oaxaca

    ()

This paper models the bias from using potential vs actual experience in log wage models. The nature of the problem is best viewed as specification error as opposed to classical errors-in-variables.We correct for the discrepancy between potential and actual work experience and create a predicted measure of work experience. We use the 1979 National Longitudinal Survey of Youth and the Panel Study of Income Dynamics and extend our findings to the Integrated Public Use Microdata Sample. Our results suggest that potential experience biases the effects of schooling and the rates of return to labor market experience. Using such a measure in earnings models underestimates the explained portion of the male–female wage gap.We are able to separately identify the decomposition biases associated with incorrect experience measures and biased parameter estimates.

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File URL: http://hdl.handle.net/10.1007/s00148-007-0180-5
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Article provided by Springer in its journal Journal of Population Economics.

Volume (Year): 22 (2009)
Issue (Month): 2 (April)
Pages: 463-499

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Handle: RePEc:spr:jopoec:v:22:y:2009:i:2:p:463-499
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  1. Bound, John & Solon, Gary, 1999. "Double trouble: on the value of twins-based estimation of the return to schooling," Economics of Education Review, Elsevier, vol. 18(2), pages 169-182, April.
  2. repec:cup:cbooks:9780521873161 is not listed on IDEAS
  3. Behrman, Jere R. & Rosenzweig, Mark R., 1999. ""Ability" biases in schooling returns and twins: a test and new estimates," Economics of Education Review, Elsevier, vol. 18(2), pages 159-167, April.
  4. Jacob Mincer & Solomon Polachek, 1974. "Family Investments in Human Capital: Earnings of Women," NBER Chapters, in: Marriage, Family, Human Capital, and Fertility, pages 76-110 National Bureau of Economic Research, Inc.
  5. Blau, Francine D & Kahn, Lawrence M, 1996. "Wage Structure and Gender Earnings Differentials: An International Comparison," Economica, London School of Economics and Political Science, vol. 63(250), pages S29-62, Suppl..
  6. Heather Antecol & Kelly Bedard, 2004. "The Racial Wage Gap: The Importance of Labor Force Attachment Differences across Black, Mexican, and White Men," Journal of Human Resources, University of Wisconsin Press, vol. 39(2).
  7. Bound, John, et al, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, vol. 12(3), pages 345-68, July.
  8. Heather Antecol & Kelly Bedard, . "The Relative Earnings of Young Mexican, Black, and White Women," Claremont Colleges Working Papers 1999-02, Claremont Colleges.
  9. 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.
  10. Ronald Oaxaca & Michael Ransom, 2003. "Using Econometric Models for Intrafirm Equity Salary Adjustments," Journal of Economic Inequality, Springer, vol. 1(3), pages 221-249, December.
  11. Jacob Mincer & Solomon Polacheck, 1974. "Family Investments in Human Capital: Earnings of Women," NBER Chapters, in: Economics of the Family: Marriage, Children, and Human Capital, pages 397-431 National Bureau of Economic Research, Inc.
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