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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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