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The Blinder–Oaxaca decomposition for linear regression models AgEcon
Jann, Ben.
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.
Tipo: Article Palavras-chave: Oaxaca; Blinder–Oaxaca decomposition; Outcome differential; Wage gap; Research Methods/ Statistical Methods.
Ano: 2008 URL: http://purl.umn.edu/122615
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The Blinder–Oaxaca decomposition for nonlinear regression models AgEcon
Sinning, Mathias; Hahn, Markus; Bauer, Thomas K..
In this article, a general Blinder–Oaxaca decomposition for nonlinear models is derived, which allows the difference in an outcome variable between two groups to be decomposed into several components. We show how, using nldecompose, this general decomposition can be applied to different models with discrete and limited dependent variables. We further demonstrate how the standard errors of the estimated components can be calculated by using Stata's bootstrap command as a prefix.
Tipo: Article Palavras-chave: Nldecompose; Blinder–Oaxaca decomposition; Nonlinear models; Research Methods/ Statistical Methods.
Ano: 2008 URL: http://purl.umn.edu/122616
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