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A bayesian approach to dynamic tobit models

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  • Steven Wei

Abstract

This paper develops a posterior simulation method for a dynamic Tobit model. The major obstacle rooted in such a problem lies in high dimensional integrals, induced by dependence among censored observations, in the likelihood function. The primary contribution of this study is to develop a practical and efficient sampling scheme for the conditional posterior distributions of the censored (i.e., unobserved) data, so that the Gibbs sampler with the data augmentation algorithm is successfully applied. The substantial differences between this approach and some existing methods are highlighted. The proposed simulation method is investigated by means of a Monte Carlo study and applied to a regression model of Japanese exports of passenger cars to the U.S. subject to a non-tariff trade barrier.

Suggested Citation

  • Steven Wei, 1999. "A bayesian approach to dynamic tobit models," Econometric Reviews, Taylor & Francis Journals, vol. 18(4), pages 417-439.
    • Handle: RePEc:taf:emetrv:v:18:y:1999:i:4:p:417-439
    DOI: 10.1080/07474939908800353
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    1. Peristiani, Stavros, 1994. "An empirical investigation of the determinants of discount window borrowing: a disaggregate analysis," Journal of Banking & Finance, Elsevier, vol. 18(1), pages 183-197, January.
    2. Dale J. Poirier & Paul A. Ruud, 1988. "Probit with Dependent Observations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 55(4), pages 593-614.
    3. 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.
    4. Geweke, J, 1993. "Bayesian Treatment of the Independent Student- t Linear Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 19-40, Suppl. De.
    5. Dagenais, Marcel G., 1982. "The Tobit model with serial correlation," Economics Letters, Elsevier, vol. 10(3-4), pages 263-267.
    6. Dale J. Poirier, 1995. "Intermediate Statistics and Econometrics: A Comparative Approach," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262161494, December.
    7. Amemiya, Takeshi, 1984. "Tobit models: A survey," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 3-61.
    8. Chib, Siddhartha, 1992. "Bayes inference in the Tobit censored regression model," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 79-99.
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    Cited by:

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    6. Peter C. Austin, 2002. "Bayesian Extensions of the Tobit Model for Analyzing Measures of Health Status," Medical Decision Making, , vol. 22(2), pages 152-162, April.
    7. Dagne Getachew & Huang Yangxin, 2012. "Bayesian inference for a nonlinear mixed-effects Tobit model with multivariate skew-t distributions: application to AIDS studies," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-24, September.
    8. Chavas, Jean-Paul & Kim, Kwansoo, 2005. "An Econometric Analysis of Price Dynamics in the Presence of a Price Floor: The Case of American Cheese," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 37(1), pages 1-15, April.
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    10. Diansheng Dong & Todd M. Schmit & Harry Kaiser, 2012. "Modelling household purchasing behaviour to analyse beneficial marketing strategies," Applied Economics, Taylor & Francis Journals, vol. 44(6), pages 717-725, February.
    11. Wei, Steven X., 2002. "A censored-GARCH model of asset returns with price limits," Journal of Empirical Finance, Elsevier, vol. 9(2), pages 197-223, March.
    12. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    13. James A. Duffy & Sophocles Mavroeidis & Sam Wycherley, 2022. "Cointegration with Occasionally Binding Constraints," Papers 2211.09604, arXiv.org, revised Jul 2023.
    14. Jean-Paul Chavas & Kwansoo Kim, 2006. "An econometric analysis of the effects of market liberalization on price dynamics and price volatility," Empirical Economics, Springer, vol. 31(1), pages 65-82, March.
    15. George Monokroussos, 2013. "A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 42(1), pages 71-105, June.
    16. Kim, Kwansoo & Chavas, Jean-Paul, 2002. "A Dynamic Analysis Of The Effects Of A Price Support Program On Price Dynamics And Price Volatility," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 27(2), pages 1-20, December.
    17. Anna Bykhovskaya & James A. Duffy, 2022. "The Local to Unity Dynamic Tobit Model," Papers 2210.02599, arXiv.org, revised Feb 2023.
    18. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    19. Dong, Diansheng & Chung, Chanjin & Kaiser, Harry M., 2001. "Panel Data Double-Hurdle Model: An Application To Dairy Advertising," 2001 Annual meeting, August 5-8, Chicago, IL 20502, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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