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Numerical Aspects of Bayesian VAR-modeling

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Author Info

  • Kadiyala, K. Rao

    (Krannert Graduate School of Management, Purdue University)

  • Karlsson, Sune

    ()
    (Dept. of Economic Statistics, Stockholm School of Economics)

Abstract

In Bayesian analysis of VAR-models, and especially in forecasting applications, the Minnesota prior of Litterman is frequently used. In many cases other prior distributions provide better forecasts and are preferable from a theoretical standpoint. This paper considers the numerical procedures needed to implement these prior distributions. In addition we also report on the forecasting performance of the different prior distributions considered in the paper.

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Bibliographic Info

Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 12.

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Length: 43 pages
Date of creation: Mar 1994
Date of revision:
Publication status: Published in Journal of Applied Econometrics, 1997, pages 99-132
Handle: RePEc:hhs:hastef:0012

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Related research

Keywords: Monte Carlo integration; importance sampling; Gibbs sampling; antithetic variates; forecasting;

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