The Review of Economics and Statistics Vol. 73 No. 1 1991
A Comparison of Two-Stage Estimators of Censored Regression Models
Abstract
This paper presents a Monte Carlo comparison of the small-sample performance of subsample ordinary least squares, the Heckman-Lee two-stage estimator, and the robust estimator of Lee. Each estimator is considered under bivariate normal, t, and chi-square error structures. The estimates indicate that the Heckman-Lee and Lee estimators do not provide an unequivocal mean square error improvement upon subsample ordinary least squares in small samples. While effectively controlling for selectivity bias, the two-stage estimators suffer a substantial loss of small-sample precision relative to subsample ordinary least squares.
- DOI
- 10.2307/2109705
- Volume
- 73
- Issue
- 1
- Pages
- 185
- Sources
- crossref openalex