Quantile regression with sample selection: Estimating women’s return to education in the U.S.
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This study uses quantile regression techniques to analyze changes in the returns to education for women. The data used is the March Current Population Survey for the years 1968, 1973, 1979, 1986 and 1990. The first step in estimating the single (linear) index selection equation uses Ichimura’s (1993) semiparametric procedure. To correct for an unknown form of a sample selection bias in the quantile regression, the second step incorporates a nonparametric method, using an idea similar to one developed by Heckman (1980) and Newey (1991) for mean regression, and Buchinsky (1998) for quantile regression.
The results show that: (a) the returns to education increased enormously for the younger cohorts, but very little for the older cohorts; (b) in general the returns are higher at the lower quantiles in the beginning of the sample period and higher at the higher quantiles by the end of the sample period; (c) there is a significant sample selection bias for all age groups at almost all quantiles; (d) toward the end of the sample period there is a significant convergence of the returns at the various quantiles, especially for the younger cohorts and age groups; and (e) the semiparametric estimates of the selection equation are considerably different from those obtained for a parametric probit model.
Key wordsQuantile Regression Nonparametric Selection Correction Return to Education.
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- Blackburn M, Bloom D, Freeman R (1993) Changes in earning differentials in the 1980’s: Concordance, convergence, causes, and consequences. In Papadimitriou DB, Wolff EN (eds.) Poverty and Prosperity in the USA in the Late Twentieth Century. St. Martin’s Press New York pp. 275–307Google Scholar
- Bound J, Johnson G (1992) Changes in the structure of wages during the 1980’s: An evaluation of alternative explanations. American Economic Review 82: 37. 1–392Google Scholar
- Bound J, Johnson G (1991) Wages in the United States during the 1980’s and beyond. In Kosters M (ed.) Workers and Their Wages ( Washington D.C.: The AEI Press ): 77–103Google Scholar
- Davis S, Haltiwanger J (1991) Wage dispersion between and within U.S. manufacturing plants 1962–1986. Brookings Papers on Economic Activity: Microeconomics: 115–180Google Scholar
- Goldin C (1990) Understanding the gender gap: An economic history of American women. Oxford University Press, New YorkGoogle Scholar
- Heckman J (1990) Varieties of sample selection bias. American Economic Review 80: 313–318Google Scholar
- Heckman J (1980) Sample selection bias as a specification error. In Stromsdorfer E, Farkas G (eds.) Evaluation Studies, Review Annual 5. Sage, Beverly Hills, pp. 61–74Google Scholar
- Katz L, Murphy K (1992) Changes in the relative wages 1963–87: Supply and demand factors. The Quarterly Journal of Economics 107: 35–78Google Scholar
- Levy F, Murnane R (1992) U.S. earnings levels and earnings inequality: A review of recent trends and proposed explanation. Journal of Economic Literature 30: 1333–1381Google Scholar
- Mincer J (1974) Schooling experience and earnings. NBER, New YorkGoogle Scholar
- Murphy K, Welch F (1991) The role of international trade in wage differentials. In Kosters M (ed.) Workers and Their Wages. The AEI Press, Washington D.C, pp. 39–69Google Scholar
- Newey W (1991) Two step series estimation of sample selection model. Unpublished manuscript, MITGoogle Scholar
- Newey W, Powell J, Walker J (1990) Semiparametric estimation of selection models: Some empirical results. American Economic Association Papers and Proceedings 80: 324–328Google Scholar