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On the ranking uncertainty of labor market wage gaps


Using a log-wage model, Horrace and Oaxaca (2001) propose estimators of the gender wage gap across industry classifications. One estimator involves the maximum over sample estimates of population parameters, and inference on this estimator follows with the implicit assumption that the sample maximum equals the population maximum. This paper proposes inference procedures for this estimator that relax this assumption. Specifically, multiple comparisons with the best methods are used to construct simultaneous confidence intervals for industry wage gaps. Using data on fourteen industry classifications, inference experiments indicate that differences in gender wage gaps across industries are insignificant at the 95% level.

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Correspondence to William C. Horrace.

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I would like to thank Dan Hamermesh, Dan Houser, Jason Hsu, Tom Kniesner, Ron Oaxaca, and Peter Schmidt for comments. All errors are mine. The generous support of the Office of the Vice Chancellor of Syracuse University is gratefully acknowledged. Responsible editor: Daniel S. Hamermesh.

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Horrace, W. On the ranking uncertainty of labor market wage gaps. J Popul Econ 18, 181–187 (2005).

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JEL classification:

  • C12
  • J31
  • J71


  • Multiple comparisons
  • wage differential
  • discrimination