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Temporal Dependence in Limited Dependent Variable Models: Theoretical and Monte-Carlo Results

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Abstract

This paper analyzes the consistency properties of classical estimators for limited dependent variables models, under conditions of serial correlation in the unobservables. A unified method of proof is used to show that for certain cases (e.g., Probit, Tobit and Normal Switching Regimes models, which are normality-based) estimators that neglect particular types of serial dependence (specifically, corresponding to the class of "mixing" processes) are still consistent. The same line of proof fails for the analogues to the above models that impose logistic distributional assumptions, thus indicating that normality plays a special role in these problems. Sets of Monte-Carlo experiments are then carried out to investigate these theoretical results.

Suggested Citation

  • Vassilis A. Hajivassiliou, 1986. "Temporal Dependence in Limited Dependent Variable Models: Theoretical and Monte-Carlo Results," Cowles Foundation Discussion Papers 803, Cowles Foundation for Research in Economics, Yale University.
    • Handle: RePEc:cwl:cwldpp:803
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    File URL: https://cowles.yale.edu/sites/default/files/files/pub/d08/d0803.pdf
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    References listed on IDEAS

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    7. Olsen, Randall J, 1978. "Note on the Uniqueness of the Maximum Likelihood Estimator for the Tobit Model," Econometrica, Econometric Society, vol. 46(5), pages 1211-1215, September.
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    1. Hajivassiliou, V A, 1994. "A Simulation Estimation Analysis of the External Debt Crises of Developing Countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(2), pages 109-131, April-Jun.

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