Wage discrimination: The case for reverse regression

Kapsalis, Constantine (2010): Wage discrimination: The case for reverse regression.

Abstract

The reverse regression method of measuring wage discrimination is the main challenge to the dominant direct regression method based on the Oaxaca/Blinder approach. In this article, it is argued that the choice between the two methods is fundamentally a choice of assumptions regarding the nature of the wage determination process and the nature of the unexplained regression residual of the wage regression equation. In particular, this article concludes that the reverse regression method is more likely to produce the correct wage discrimination measure if any of the following three assumptions is correct: (a) qualifications do not determine how much individuals earn (as the direct regression method assumes) but, instead, determine which candidates are selected for existing jobs with fixed wages; (b) errors in the measurement of qualifications are larger than errors in the measurement of wages, in which case the direct regression method would understate the importance of differences in qualifications; and (c) differences in unobserved qualifications (e.g., importance of job flexibility; relevance of past work experience) between two groups are not zero (as the direct regression method assumes) but tend to favour the group with the better observed qualifications. Finally, this article shows that application of the reverse regression technique simply requires the augmentation of the qualification component of the direct regression method by dividing it by the R2 coefficient.

• Item Type: MPRA Paper
• Language: English
• Keywords: wage discrimination; gender discrimination
• Subjects: J - Labor and Demographic Economics > J7 - Labor Discrimination

References

Bender, A. K, S.M. Donohue, and J.S. Heywood, 2005. “Job satisfaction and gender segregation.” Oxford Economic Papers 57: 479–496.

Blinder, A., 1973. “Wage discrimination: Reduced form and structural estimates.” Journal of Human Resources 8 (Fall): 436-455.

Conway, D.A. and H.V. Roberts, 1983. “Reverse regression, fairness, and employment discrimination.” Journal of Business and Economic Statistics, January: 75-85.

Dempsters, A.P., 1979. Statistical concepts of discrimination. Statistics Department, Harvard University, Cambridge, MA.

Goldberger, A.S., 1984. “Reverse regression and salary discrimination.” Journal of Human Resources XIX, 3.

Kapsalis, C., 1979. A new method of estimating wage discrimination between men and women. Economic Council of Canada.

Kapsalis, C., 1982. “A new measure of wage discrimination.” Economics Letters 9: 287-293.

Oaxaca, R., 1973. “Male-female wage differential in urban labour markets.” International Economic Review 14 (3): 693-705.

Roberts, H.V., 1980. “Statistical biases in the measurement of employment discrimination.” In E.R. Livernash, ed., Comparable worth: Issues and alternatives. Equal Employment Advisory Council, Washington, DC.

Weichselbaumer, D. and R. Winter-Ebmer, 2005. “A meta-analysis of the international gender wage gap.” Journal of Economic Surveys 9 (3): 479-511.

White, F.P. and M.J. Piette, 1998. “The use of ‘reverse regression’ in employment discrimination analysis.” Journal of Forensic Economics 11(2): 127-138.