Foul or Fair? : The Heckman Correction for Sample Selection and its Critique - A Short Survey


Puhani, Patrick A.


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URL: http://ub-madoc.bib.uni-mannheim.de/704
URN: urn:nbn:de:bsz:180-madoc-7047
Document Type: Working paper
Year of publication: 1997
Publication language: English
Institution: Sonstige Einrichtungen > ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung
MADOC publication series: Veröffentlichungen des ZEW (Leibniz-Zentrum für Europäische Wirtschaftsforschung) > ZEW Discussion Papers
Subject: 330 Economics
Subject headings (SWD): Monte-Carlo-Simulation , Auswahl
Abstract: 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.
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Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt.




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Puhani, Patrick A. (1997) Foul or Fair? : The Heckman Correction for Sample Selection and its Critique - A Short Survey. Open Access [Working paper]
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