More on Identification in Detailed Wage Decompositions

By Javier Gardeazabal, A. Ugidos. Review of Economics and Statistics, 2002

241 citations recorded by the source corpus.

Wage decompositions are often used to decompose wage differentials of two demographic groups into differences in characteristics and differences in returns to those characteristics. The latter part is used as an estimate of the degree of discrimination. A problem with this approach is that the contributions of individual dummy variables to the wage decomposition are not identified. This note proposes a simple solution to the identification problem. The solution is illustrated with an empirical application to Spanish labor market data.

Subfields: Demography, Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/f57d077098bb6fd5aaed0f9a855a8488234009f3

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Citations in the corpus

When Do Covariates Matter? And Which Ones, and How Much? (2016, background): “Gardeazabal and Ugidos (2004), Yun (2005), and Fortin (2008) suggest various approaches to dealing with the issue raised in Oaxaca and Ransom (1999).”
A Stata implementation of the Blinder-Oaxaca decomposition (2008, methodology): “Hence, there is still some arbitrariness in the method by Gardeazabal and Ugidos (2004) and Yun (2005b).”
Decomposing Wage Distributions using Recentered Influence Function Regressions (2018, background): “A well-known difficulty discussed by Oaxaca and Ransom (1999) and Gardeazabal and Ugidos (2004) is that the contribution of each covariate to the wage structure effect, E [ Xk|T = 1 ] [ β1,k − β0,k ] , is highly sensitive to the choice of the base group.3 A second limitation discussed by Barsky et…”
Decomposing the Ins and Outs of Cyclical Unemployment (2012, unknown): “having omitted reference categories (Gardeazabal and Ugidos, 2004; Yun, 2005), it complicates the economic interpretation of the decomposition results (Gelbach, 2002; Fortin et al.”
Identification problem and detailed Oaxaca decomposition: A general solution and inference (2008, unknown): “Furthermore, Gardeazaba and Ugidos [3] point out that the constraints Suits [8] uses are quite common underlying assumptions in linear models, though they are not explicitly expressed.”