Please use this identifier to cite or link to this item:
Puhani, Patrick A.
Year of Publication: 
Series/Report no.: 
ZEW Discussion Papers 97-07
This paper gives a short overview of Monte Carlo studies on the usefulness of Heckman’s (1976, 1979) two–step estimator for estimating a selection model. It shows that exploratory work to check for collinearity problems is strongly recommended before deciding on which estimator to apply. In the absence of collinearity problems, the full–information maximum likelihood estimator is preferable to the limited–information two–step method of Heckman, although the latter also gives reasonable results. If, however, collinearity problems prevail, subsample OLS (or the Two–Part Model) is the most robust amongst the simple–to–calculate estimators.
Document Type: 
Working Paper

Files in This Item:
77.46 kB

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.