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Unexplained Gaps and Oaxaca-Blinder Decompositions

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  • Todd E. Elder
  • John H. Goddeeris
  • Steven J. Haider

Abstract

We analyze four methods to measure unexplained gaps in mean outcomes: three decompositions based on the seminal work of Oaxaca (1973) and Blinder (1973) and an approach involving a seemingly naïve regression that includes a group indicator variable. Our analysis yields two principal findings. We first show that a commonlyused pooling decomposition systematically overstates the contribution of observable characteristics to mean outcome differences, therefore understating unexplained differences. We also show that the coefficient on a group indicator variable from an OLS regression is an attractive approach for obtaining a single measure of the unexplained gap. We then provide three empirical examples that explore the practical importance of our analytic results.

Suggested Citation

  • Todd E. Elder & John H. Goddeeris & Steven J. Haider, 2009. "Unexplained Gaps and Oaxaca-Blinder Decompositions," CEPR Discussion Papers 600, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    • Handle: RePEc:auu:dpaper:600
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    File URL: https://www.cbe.anu.edu.au/researchpapers/cepr/DP600.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    decompositions; discrimination;

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

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