Blinder-Oaxaca decomposition for Tobit models
AbstractIn this article, a decomposition method for Tobit models is derived, which allows the differences in observed outcome variables between two groups to be decomposed into a part that is explained by differences in observed characteristics and a part attributable to differences in the estimated coefficients. Monte Carlo simulations demonstrate that in the case of censored dependent variables this decomposition method produces more reliable results than the conventional Blinder-Oaxaca decomposition for linear regression models. Finally, our method is applied to a decomposition of the gender wage gap using German data.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics.
Volume (Year): 42 (2010)
Issue (Month): 12 ()
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Other versions of this item:
- Thomas Bauer & Mathias Sinning, 2005. "Blinder-Oaxaca Decomposition for Tobit Models," RWI Discussion Papers 0032, Rheinisch-Westfälisches Institut für Wirtschaftsforschung.
- Bauer, Thomas & Sinning, Mathias, 2005. "Blinder-Oaxaca Decomposition for Tobit Models," CEPR Discussion Papers 5309, C.E.P.R. Discussion Papers.
- Bauer, Thomas K. & Sinning, Mathias, 2005. "Blinder-Oaxaca Decomposition for Tobit Models," IZA Discussion Papers 1795, Institute for the Study of Labor (IZA).
- C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models
- J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
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