An Alternative Estimator for Industrial Gender Wage Gaps: A Normalized Regression Approach

Myeong-Su Yun (msyun@inha.ac.kr) and Eric Lin

No 9381, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Using normalized regression equations, we propose an alternative estimator of industrial gender wage gaps which is identified in the sense that it is invariant to the choice of an unobserved non-discriminatory wage structure, and to the choice of the reference groups of any categorical variables. The proposed estimator measures the pure impact of industry on gender wage gaps after netting out wage differentials due to differences in characteristics and their coefficients between men and women. Furthermore, the proposed estimator is easy to implement, including hypothesis tests. We compare the proposed estimator with existing estimators using samples from 1998 Current Population Survey of US.

Keywords: gender wage discrimination; Oaxaca decomposition; identification; industrial gender wage gaps; normalized regression (search for similar items in EconPapers)
JEL-codes: C12 J31 J71 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2015-09
New Economics Papers: this item is included in nep-ecm
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Published - published in: Pacific Economic Review, 2015, 20(4), 569-587

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Journal Article: Alternative Estimator for Industrial Gender Wage Gaps: A Normalized Regression Approach (2015)
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