Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
On the ranking uncertainty of labor market wage gaps
Abstract. 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.
On the ranking uncertainty of labor market wage gaps
Abstract. 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.
On the ranking uncertainty of labor market wage gaps
Horrace, William C. (Autor:in)
2005
Aufsatz (Zeitschrift)
Englisch
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