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The "Pathology" Of The Natural Conjugate Prior Density In The Regression Model

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Author Info

  • BAUWENS, L.

Abstract

In a Bayesian analysis of the linear regression model, one may have prior information on the error variance. If one incorporates this kind of information in a natural conjugate prior density, under certain conditions the posterior mean of the coefficients on which one is informative is equal to a constrained least squares estimator. The value of the posterior covariance matrix is also studied. We discuss and illustrate how to avoid getting posterior results too close to the “pathological” results summarized above.

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Bibliographic Info

Paper provided by Universite Aix-Marseille III in its series G.R.E.Q.A.M. with number 90a14.

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Length: 19 pages
Date of creation: 1990
Date of revision:
Handle: RePEc:fth:aixmeq:90a14

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Keywords: regression analysis ; linear models ; econometrics;

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Cited by:
  1. Carmen Fernandez & Eduardo Ley & Mark F.J. Steel, 1998. "Benchmark Priors for Bayesian Model Averaging," Econometrics 9804001, EconWPA, revised 31 Jul 1999.

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