An Extension of the Blinder-Oaxaca Decomposition Technique to Logit and Probit Models
The Blinder-Oaxaca decomposition technique is widely used to identify and quantify the separate contributions of group differences in measurable characteristics, such as education, experience, marital status, and geographical differences to racial and gender gaps in outcomes. The technique cannot be used directly, however, if the outcome is binary and the coefficients are from a logit or probit model. I describe a relatively simple method of performing a decomposition that uses estimates from a logit or probit model. Expanding on the original application of the technique in Fairlie (1999), I provide a more thorough discussion of how to apply the technique, an analysis of the sensitivity of the decomposition estimates to different parameters, and the calculation of standard errors.
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- Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
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Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
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- Oaxaca, Ronald L. & Ransom, Michael R., 1994. "On discrimination and the decomposition of wage differentials," Journal of Econometrics, Elsevier, vol. 61(1), pages 5-21, March.
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