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Simulated Classical Tests in the Multiperiod Multinomial Probit Model

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Author Info
Ziegler, Andreas
Abstract

This paper compares different versions of the simulated counterparts of the Wald test, the score test, and the likelihood ratio test in the multiperiod multinomial probit model. Monte Carlo experiments show that the simple form of the simulated likelihood ratio test delivers the most favorable test results in the five-period three-alternative probit model considered here. This result applies to the deviation of the frequency of type I errors from the given significance levels as well as to the frequency of type II errors. In contrast, the inclusion of the quasi maximum likelihood theory into the simulated likelihood ratio test leads to substantial computational problems. The combination of this theory with the simulated Wald test or the simulated score test also produces no general advantages over the other versions of these two simulated classical tests. Neither an increase in the number of observations nor a rise in the number of random draws in the considered GHK simulator systematically lead to a more precise conformity between the frequency of type I errors and the basic significance levels. An increase in the number of observations merely reduces the frequency of type II errors. --

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Paper provided by ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research in its series ZEW Discussion Papers with number 02-38.

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Date of creation: 2002
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Handle: RePEc:zbw:zewdip:860

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Related research
Keywords: Simulated classical tests; multiperiod multinomial probit model; Monte Carlo simulation;

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Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models

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  1. Axel Borsch-Supan & Vassilis Hajivassiliou & Laurence J. Kotlikoff & John N. Morris, 1990. "Health, Children, and Elderly Living Arrangements: A Multiperiod-Multinomial Probit Model with Unobserved Heterogeneity and Autocorrelated Errors," NBER Working Papers 3343, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  2. Lee, Lung-fei, 1999. "Statistical Inference With Simulated Likelihood Functions," Econometric Theory, Cambridge University Press, vol. 15(03), pages 337-360, June. [Downloadable!]
  3. Bolduc, Denis & Lacroix, Guy & Muller, Christophe, 1996. "The choice of medical providers in rural Benin: A comparison of discrete choice models," Journal of Health Economics, Elsevier, vol. 15(4), pages 477-498, August. [Downloadable!] (restricted)
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  4. Guilkey, David K. & Murphy, James L., 1993. "Estimation and testing in the random effects probit model," Journal of Econometrics, Elsevier, vol. 59(3), pages 301-317, October. [Downloadable!] (restricted)
  5. John Geweke & Michael Keane & David Runkle, 1994. "Alternative computational approaches to inference in the multinomial probit model," Staff Report 170, Federal Reserve Bank of Minneapolis. [Downloadable!]
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  6. Davidson, Russell & MacKinnon, James G., 1984. "Convenient specification tests for logit and probit models," Journal of Econometrics, Elsevier, vol. 25(3), pages 241-262, July. [Downloadable!] (restricted)
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  7. Vijverberg, Wim P. M., 1997. "Monte Carlo evaluation of multivariate normal probabilities," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 281-307. [Downloadable!] (restricted)
  8. Geweke, John F. & Keane, Michael P. & Runkle, David E., 1997. "Statistical inference in the multinomial multiperiod probit model," Journal of Econometrics, Elsevier, vol. 80(1), pages 125-165, September. [Downloadable!] (restricted)
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  9. 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. [Downloadable!] (restricted)
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  10. Vassilis A. Hajivassiliou & Daniel L. McFadden, 1998. "The Method of Simulated Scores for the Estimation of LDV Models," Econometrica, Econometric Society, vol. 66(4), pages 863-896, July.
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  11. Lechner, Michael, 1995. "Some Specification Tests for Probit Models Estimated on Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(4), pages 475-88, October.
  12. Asea, Patrick K. & Turnovsky, Stephen J., 1998. "Capital income taxation and risk-taking in a small open economy," Journal of Public Economics, Elsevier, vol. 68(1), pages 55-90, April. [Downloadable!] (restricted)
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  13. Gourieroux, Christian & Monfort, Alain, 1993. "Simulation-based inference : A survey with special reference to panel data models," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 5-33, September. [Downloadable!] (restricted)
  14. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January. [Downloadable!] (restricted)
  15. 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. [Downloadable!] (restricted)
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