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Including Prior Information in Probit Model Estimation

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  • William E. Griffiths
  • R. Carter Hill
  • Christopher J. O'Donnell

Abstract

The effects of including different kinds of prior information in estimation of the probit model is examined within the framework of Bayesian inference. Of interest is the effect on posterior information for coefficients, probabilities and elasticities. In a model designed to explain choice between fixed and variable interest-rate mortgages, we show that using Bayesian inference to include inequality information on the signs of coefficients yields inferences about probabilities and elasticities that are substantially different from those obtained using maximum likelihood estimation. In a second model, concerned with state voting behavior, we find that putting prior information on probabilities, rather than coefficients, has a dramatic effect on the posterior density functions for the model coefficients, probabilities and elasticities.

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Bibliographic Info

Paper provided by The University of Melbourne in its series Department of Economics - Working Papers Series with number 816.

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Length: 28 pages
Date of creation: 2001
Date of revision:
Handle: RePEc:mlb:wpaper:816

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Related research

Keywords: Inequality restrictions; Metropolis-Hastings algorithm; Voting choice; Mortgage choice;

References

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  1. 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.
  2. Frank Kleibergen & Herman K. van Dijk, 1998. "Bayesian Simultaneous Equations Analysis using Reduced Rank Structures," Tinbergen Institute Discussion Papers 98-025/4, Tinbergen Institute.
  3. Sims,Christopher A. (ed.), 1996. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521566094, October.
  4. Amemiya, Takeshi, 1981. "Qualitative Response Models: A Survey," Journal of Economic Literature, American Economic Association, vol. 19(4), pages 1483-1536, December.
  5. Sims,Christopher A. (ed.), 1996. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521566100, October.
  6. 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.
  7. Zellner, Arnold & Rossi, Peter E., 1984. "Bayesian analysis of dichotomous quantal response models," Journal of Econometrics, Elsevier, vol. 25(3), pages 365-393, July.
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Cited by:
  1. Francisco-José Polo & Miguel Negrín & Xavier Badía & Montse Roset, 2005. "Bayesian regression models for cost-effectiveness analysis," The European Journal of Health Economics, Springer, vol. 6(1), pages 45-52, March.

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