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When does Heckman’s two-step procedure for censored data work and when does it not?

  • Jonsson, Robert

    ()

    (Department of Economics, School of Business, Economics and Law, University of Gothenburg)

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    Heckman’s two-step procedure (Heckit) for estimating the parameters in linear models from censored data is frequently used by econometricians, despite of the fact that earlier studies cast doubt on the procedure. In this paper it is shown that estimates of the hazard h for approaching the censoring limit, the latter being used as an explanatory variable in the second step of the Heckit, can induce multicollinearity. The influence of the censoring proportion and sample size upon bias and variance in three types of random linear models are studied by simulations. From these results a simple relation is established that describes how absolute bias depends on the censoring proportion and the sample size. It is also shown that the Heckit may work with non-normal (Laplace) distributions, but it collapses if h deviates too much from that of the normal distribution. Data from a study of work resumption after sick-listing are used to demonstrate that the Heckit can be very risky.

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    File URL: http://hdl.handle.net/2077/9593
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    Paper provided by Statistical Research Unit, Department of Economics, School of Business, Economics and Law, University of Gothenburg in its series Research Reports with number 2008:2.

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    Length: 22 pages
    Date of creation: 22 Feb 2008
    Date of revision:
    Handle: RePEc:hhs:gunsru:2008_002
    Contact details of provider: Postal:
    Statistical Research Unit, University of Gothenburg, Box 640, SE 40530 GÖTEBORG

    Web page: http://www.statistics.gu.se/

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    1. Frisén, Marianne & Andersson, Eva & Schiöler, Linus, 2007. "Robust outbreak surveillance of epidemics in Sweden," Research Reports 2007:12, Statistical Research Unit, Department of Economics, School of Business, Economics and Law, University of Gothenburg.
    2. Newey, Whitney K., 2001. "Conditional Moment Restrictions In Censored And Truncated Regression Models," Econometric Theory, Cambridge University Press, vol. 17(05), pages 863-888, October.
    3. Puhani, Patrick A, 2000. " The Heckman Correction for Sample Selection and Its Critique," Journal of Economic Surveys, Wiley Blackwell, vol. 14(1), pages 53-68, February.
    4. Nelson, Forrest D., 1984. "Efficiency of the two-step estimator for models with endogenous sample selection," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 181-196.
    5. Yuzo Honda, 1985. "Testing the Error Components Model with Non-Normal Disturbances," Review of Economic Studies, Oxford University Press, vol. 52(4), pages 681-690.
    6. Rosett, Richard N & Nelson, Forrest D, 1975. "Estimation of the Two-Limit Probit Regression Model," Econometrica, Econometric Society, vol. 43(1), pages 141-46, January.
    7. Paarsch, Harry J., 1984. "A Monte Carlo comparison of estimators for censored regression models," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 197-213.
    8. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492 National Bureau of Economic Research, Inc.
    9. Lennart Flood & Urban Gråsjo, 2001. "A Monte Carlo simulation study of Tobit models," Applied Economics Letters, Taylor & Francis Journals, vol. 8(9), pages 581-584.
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