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Foul or Fair? The Heckman Correction for Sample Selection and Its Critique. A Short Survey

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  • Puhani, Patrick A.

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.

Suggested Citation

  • Puhani, Patrick A., 1997. "Foul or Fair? The Heckman Correction for Sample Selection and Its Critique. A Short Survey," ZEW Discussion Papers 97-07, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  • Handle: RePEc:zbw:zewdip:5116
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    References listed on IDEAS

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    1. Uschi Backes-Gellner & Johannes Mure & Simone Tuor, 2006. "The Puzzle of Non-Participation in Continuing Training – An Empirical Study of Permanent vs. Occasional Non-Participation," Working Papers 0058, University of Zurich, Institute for Strategy and Business Economics (ISU).

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