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The Blinder-Oaxaca decomposition for nonlinear regression models

Authors: Sinning, Mathias; Hahn, Markus; Bauer, Thomas K.;

The Blinder-Oaxaca decomposition for nonlinear regression models

Abstract

In this article, a general Blinder-Oaxaca decomposition for non-linear 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.

Country
Australia
Keywords

Differentials, Employment, Nonlinear models, Keywords: Blinder-Oaxaca decomposition, Blinder Oaxaca decomposition, Wage Discrimination, Nldecompose, Nonlinear Models, st0152, nldecompose

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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