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On the Tradeoff between Computational Simplicity and Asymptotic Properties in Multivariate Probit

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  • Kimhi, Ayal

Abstract

This paper discusses the most efficient estimator among Quasi Maximum Likelihood Estimators using at most two levels of numerical integration, for the multivariate probit model. Simulations show that this estimator is more efficient but not more costly than the second-best alternative. However, its added efficiency depends on the correlation structure. Citation Copyright 1999 by Kluwer Academic Publishers.

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  • Kimhi, Ayal, 1999. "On the Tradeoff between Computational Simplicity and Asymptotic Properties in Multivariate Probit," Computational Economics, Springer;Society for Computational Economics, vol. 13(1), pages 93-101, February.
    • Handle: RePEc:kap:compec:v:13:y:1999:i:1:p:93-101
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    Cited by:

    1. Yen, Steven T. & Yuan, Yan & Liu, Xiaowen, 2009. "Alcohol consumption by men in China: A non-Gaussian censored system approach," China Economic Review, Elsevier, vol. 20(2), pages 162-173, June.
    2. Baltas, George, 2004. "A model for multiple brand choice," European Journal of Operational Research, Elsevier, vol. 154(1), pages 144-149, April.
    3. Anton, Wilma Rose Q., 2005. "The Choice of Management Practices: What Determines the Design of an Environmental Management System?," 2005 Annual meeting, July 24-27, Providence, RI 19503, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Sorada Tapsuwan & Michael Burton & James Perriam, 2010. "A Multivariate Probit Analysis of Willingness to Pay for Cave Conservation: A Case Study of Yanchep National Park, Western Australia," Tourism Economics, , vol. 16(4), pages 1019-1035, December.
    5. Steven T. Yen & Biing‐Hwan Lin, 2008. "Quasi‐maximum likelihood estimation of a censored equation system with a copula approach: meat consumption by U.S. individuals," Agricultural Economics, International Association of Agricultural Economists, vol. 39(2), pages 207-217, September.

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