Computational Issues in the Sequential Probit Model: A Monte Carlo Study
AbstractWe discuss computational issues in the sequential probit model that have limited its use in applied research. We estimate parameters of the model by the method of simulated maximum likelihood (SML) and by Bayesian MCMC algorithms. We provide Monte Carlo evidence on the relative performance of both estimators and find that the SML procedure computes standard errors of the estimated correlation coefficients that are less reliable. Given the numerical difficulties associated with the estimation procedures, we advise the applied researcher to use both the stochastic optimization algorithm in the Simulated Maximum Likelihood approach and the Bayesian MCMC algorithm to check the compatibility of the results. Copyright Springer Science + Business Media, Inc. 2005
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Bibliographic InfoArticle provided by Society for Computational Economics in its journal Computational Economics.
Volume (Year): 26 (2005)
Issue (Month): 2 (October)
Metropolis–Gibbs; sequential probit; simulated maximum likelihood; simulated annealing;
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- Cannings, Kathy & Montmarquette, Claude & Mahseredjian, Sophie, 1996.
"Entrance quotas and admission to medical schools: a sequential probit model,"
Economics of Education Review,
Elsevier, vol. 15(2), pages 163-174, April.
- Cannings, K. & Montmarquette, C. & Mahseredjian, S., 1994. "Entrance Quotas abs Admission to Medical Schools: A Sequential Probit Model," Cahiers de recherche 9418, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Kathy Cannings & Sophie Mahseredjian & Claude Montmarquette, 1994. "Entrance Quotas and Admission to Medical Schools: A Sequential Probit Model," CIRANO Working Papers 94s-10, CIRANO.
- Cannings, K. & Montmarquette, C. & Mahseredjian, S., 1994. "Entrance Quotas abs Admission to Medical Schools: a Sequential Probit Model," Cahiers de recherche 9418, Universite de Montreal, Departement de sciences economiques.
- John Geweke & Michael Keane & David Runkle, 1994.
"Alternative computational approaches to inference in the multinomial probit model,"
170, Federal Reserve Bank of Minneapolis.
- Geweke, John & Keane, Michael P & Runkle, David, 1994. "Alternative Computational Approaches to Inference in the Multinomial Probit Model," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 609-32, November.
- Hajivassiliou, Vassilis & McFadden, Daniel & Ruud, Paul, 1996.
"Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results,"
Journal of Econometrics,
Elsevier, vol. 72(1-2), pages 85-134.
- Vassilis A. Hajivassiliou & Daniel L. McFadden & Paul Ruud, 1993. "Simulation of Multivariate Normal Rectangle Probabilities and their Derivatives: Theoretical and Computational Results," Working Papers _024, Yale University.
- Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
- Monjon, Stephanie & Waelbroeck, Patrick, 2003. "Assessing spillovers from universities to firms: evidence from French firm-level data," International Journal of Industrial Organization, Elsevier, vol. 21(9), pages 1255-1270, November.
- Schmidt, Peter, 1977. "Estimation of seemingly unrelated regressions with unequal numbers of observations," Journal of Econometrics, Elsevier, vol. 5(3), pages 365-377, May.
- McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240.
- Keane, Michael P, 1992. "A Note on Identification in the Multinomial Probit Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 193-200, April.
- Maksym, Obrizan, 2010. "A Bayesian Model of Sample Selection with a Discrete Outcome Variable," MPRA Paper 28577, University Library of Munich, Germany.
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