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Unexplained Gaps and Oaxaca-Blinder Decompositions

Author

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  • Elder, Todd E.

    () (Michigan State University)

  • Goddeeris, John H.

    () (Michigan State University)

  • Haider, Steven J.

    () (Michigan State University)

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 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 also show that a commonly-used pooling decomposition systematically overstates the contribution of observable characteristics to mean outcome differences when compared to OLS regression, therefore understating unexplained differences. We then provide three empirical examples that explore the practical importance of our analytic results.

Suggested Citation

  • Elder, Todd E. & Goddeeris, John H. & Haider, Steven J., 2009. "Unexplained Gaps and Oaxaca-Blinder Decompositions," IZA Discussion Papers 4159, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp4159
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    References listed on IDEAS

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    More about this item

    Keywords

    decompositions; discrimination;

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • 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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