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A Comparison of Alternative Estimators for Binary Panel Probit Models

Author

Listed:
  • Harris, M.N.
  • Macquarie, L.R.
  • Siouclis, A.J.

Abstract

Recent advances in computing power have brought the use of computer intensive estimation methods of binary panel data models within the reach of the applied researcher. The aim of this paper is to apply some of these techniques to a marleting data set and compare the results. In addition, their small sample performance is examined via Monte Carlo simulation experiments. The first estimation technique used was maximum likelihood estimation of the cross section probit (ignoring heterogeneity).

Suggested Citation

  • Harris, M.N. & Macquarie, L.R. & Siouclis, A.J., 1998. "A Comparison of Alternative Estimators for Binary Panel Probit Models," Monash Econometrics and Business Statistics Working Papers 4/98, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:1998-4
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    Cited by:

    1. Elena Bardasi & Chiara Monfardini, 2004. "Women's Employment, Children and Transition: An Empirical Analysis on Poland," Eastward Enlargement of the Euro-zone Working Papers wp25, Free University Berlin, Jean Monnet Centre of Excellence, revised 15 Oct 2004.

    More about this item

    Keywords

    MODELS ; COMPUTERS ; MAXIMUM LIKELIHOOD;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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