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Semiparametric Estimation of the Intercept of a Sample Selection Model

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  • Donald W. K. Andrews
  • Marcia M. A. Schafgans

Abstract

This paper provides a consistent and asymptotically normal estimator for the intercept of a semiparametrically estimated sample selection model. The estimator uses a decreasingly small fraction of all observations as the sample size goes to infinity, as in Heckman (1990). In the semiparametrics literature, estimation of the intercept has typically been subsumed in the nonparametric sample selection bias correction term. The estimation of the intercept, however, is important from an economic perspective. For instance, it permits one to determine the "wage gap" between unionized and nonunionized workers, decompose the wage differential between different socioeconomic groups (e.g. male-female and black-white), and evaluate the net benefits of a social programme.

Suggested Citation

  • Donald W. K. Andrews & Marcia M. A. Schafgans, 1998. "Semiparametric Estimation of the Intercept of a Sample Selection Model," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 497-517.
  • Handle: RePEc:oup:restud:v:65:y:1998:i:3:p:497-517.
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    File URL: http://hdl.handle.net/10.1111/1467-937X.00055
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