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Multivariate probit regression using simulated maximum likelihood

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  • Lorenzo Cappellari

    (Università del Piemonte Orientale and University of Essex)

  • Stephen P. Jenkins

    () (University of Essex)

Abstract

We discuss the application of the GHK simulation method to maximum likelihood estimation of the multivariate probit regression model, and describe and illustrate a Stata program mvprobit for this purpose.

Suggested Citation

  • Lorenzo Cappellari & Stephen P. Jenkins, 2003. "Multivariate probit regression using simulated maximum likelihood," United Kingdom Stata Users' Group Meetings 2003 10, Stata Users Group.
  • Handle: RePEc:boc:usug03:10
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    File URL: http://fmwww.bc.edu/repec/usug2003/Capelari_Jenkins-UKSUG2003.pdf
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    1. Borsch-Supan, Axel & Hajivassiliou, Vassilis A., 1993. "Smooth unbiased multivariate probability simulators for maximum likelihood estimation of limited dependent variable models," Journal of Econometrics, Elsevier, vol. 58(3), pages 347-368, August.
    2. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
    3. V A Hajivassiliou, 1997. "Some Practical Issues in Maximum Simulated Likelihood," STICERD - Econometrics Paper Series 340, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
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