Semiparametric Estimation of a Sample Selection Model
AbstractThis 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 typically has 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 program.
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Bibliographic InfoPaper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1119.
Length: 35 pages
Date of creation: Mar 1996
Date of revision:
Publication status: Published in Review of Economic Studies (1998), 65: 497-517
Note: CFP 965.
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Web page: http://cowles.econ.yale.edu/
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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA
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- repec:ese:iserwp:2000-07 is not listed on IDEAS
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