The Blinder–Oaxaca Decomposition for Linear Regression Models

The Blinder–Oaxaca Decomposition for Linear Regression Models

The counterfactual decomposition technique popularized by Blinder (1973, Journal of Human Resources, 436–455) and Oaxaca (1973, International Economic Review, 693–709) is widely used to study mean outcome differences between groups. For example, the technique is often used to analyze wage gaps by se...

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Veröffentlicht in:The Stata journal 2008-12, Vol.8 (4), p.453-479
1. Verfasser: Jann, Ben
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Regression analysis
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description The counterfactual decomposition technique popularized by Blinder (1973, Journal of Human Resources, 436–455) and Oaxaca (1973, International Economic Review, 693–709) is widely used to study mean outcome differences between groups. For example, the technique is often used to analyze wage gaps by sex or race. This article summarizes the technique and addresses several complications, such as the identification of effects of categorical predictors in the detailed decomposition or the estimation of standard errors. A new command called oaxaca is introduced, and examples illustrating its usage are given.
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subjects Regression analysis
title The Blinder–Oaxaca Decomposition for Linear Regression Models
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