Semiparametric Estimation of the Intercept of a Sample Selection Model

S-Tier
Journal: Review of Economic Studies
Year: 1998
Volume: 65
Issue: 3
Pages: 497-517

Authors (2)

Donald W. K. Andrews (Yale University) Marcia M. A. Schafgans (not in RePEc)

Score contribution per author:

4.022 = (α=2.01 / 2 authors) × 4.0x S-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:oup:restud:v:65:y:1998:i:3:p:497-517.
Journal Field
General
Author Count
2
Added to Database
2026-01-24