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Monte Carlo Investigation of the Initial Values Problem in Censored Dynamic Random-Effects Panel Data Models

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  • Akay, Alpaslan

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

Abstract

Three designs of Monte Carlo experiments are used to investigate the initial-value problem in censored dynamic random-effects (Tobit type 1) models. We compared three widely used solution methods: naive method based on exogenous initial values assumption; Heckman's approximation; and the simple method of Wooldridge. The results suggest that the initial values problem is a serious issue: using a method which misspecifies the conditional distribution of initial values can cause misleading results on the magnitude of true (structural) and spurious state-dependence. The naive exogenous method is substantially biased for panels of short duration. Heckman's approximation works well. The simple method of Wooldridge works better than naive exogenous method in short panels, but it is not as good as Heckman's approximation. It is also observed that these methods performs equally well for panels of long duration.

Suggested Citation

  • Akay, Alpaslan, 2007. "Monte Carlo Investigation of the Initial Values Problem in Censored Dynamic Random-Effects Panel Data Models," Working Papers in Economics 278, University of Gothenburg, Department of Economics.
  • Handle: RePEc:hhs:gunwpe:0278
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    File URL: http://hdl.handle.net/2077/7621
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    References listed on IDEAS

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    More about this item

    Keywords

    Initial value problem; Dynamic Tobit model; Monte Carlo experiment; Heckman's approximation; Simple method of Wooldridge;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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