Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/103844
Authors: 
Kaiser, Boris
Year of Publication: 
2013
Series/Report no.: 
Discussion Papers, Department of Economics, Universität Bern 13-08
Abstract: 
When decomposing differences in average economic outcome between two groups of individuals, it is common practice to base the analysis on logarithms if the dependent variable is nonnegative. This paper argues that this approach raises a number of undesired statistical and conceptual issues because decomposition terms have the interpretation of approximate percentage differences in geometric means. Instead, we suggest that the analysis should be based on the arithmetic means of the original dependent variable. We present a flexible parametric decomposition framework that can be used for all types of continuous (or count) connegative dependent variables. In particular, we derive a propensity-score-weighted estimator for the aggregate decomposition that is 'doubly robust', that is, consistent under two separate sets of assumptions. A comparative Monte Carlo study illustrates that the proposed estimator performs well in a many situations. An application to the union wage gap in the United States finds that the importance of the unexplained union wage premium is much smaller than suggested by the standard log-wage decomposition.
Subjects: 
Oaxaca-Blinder
Decomposition Methods
Quasi-Maximum-Likelihood
Doubly Robust Estimation
Arithmetic and Geometric Means
Inverse Probability Weighting
JEL: 
C10
C50
C51
J31
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.