Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/58752 
Year of Publication: 
2012
Series/Report no.: 
IZA Discussion Papers No. 6397
Publisher: 
Institute for the Study of Labor (IZA), Bonn
Abstract: 
This paper proposes a decomposition of the composition effect, i.e. the part of the observed between-group difference in the distribution of some economic outcome that can be explained by differences in the distribution of covariates. Our decomposition contains three types of components: (i) the direct contributions of each covariate due to between-group differences in the respective marginal distributions, (ii) several two way and higher order interaction effects due to the interplay between two or more covariates' marginal distributions, and (iii) a dependence effect accounting for between-group differences in dependence patterns among the covariates. Our methods can be used to decompose differences in arbitrary distributional features, like quantiles or inequality measures, and allows for general nonlinear relationships between the outcome and the covariates. It can easily be implemented in practice using standard econometric techniques. An application to wage data from the US illustrates the empirical relevance of the decomposition's components.
Subjects: 
counterfactual distribution
decomposition methods
JEL: 
C13
C18
C21
J31
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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