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Forecasting with Bayesian Vector Autoregressions

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  • Karlsson, Sune

    ()
    (Department of Business, Economics, Statistics and Informatics)

Abstract

Prepared for the Handbook of Economic Forecasting, vol 2 This chapter reviews Bayesian methods for inference and forecasting with VAR models. Bayesian inference and, by extension, forecasting depends on numerical methods for simulating from the posterior distribution of the parameters and spe- cial attention is given to the implementation of the simulation algorithm.

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Bibliographic Info

Paper provided by Örebro University, School of Business in its series Working Papers with number 2012:12.

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Length: 105 pages
Date of creation: 04 Aug 2012
Date of revision:
Handle: RePEc:hhs:oruesi:2012_012

Contact details of provider:
Postal: Örebro University School of Business, SE - 701 82 ÖREBRO, Sweden
Phone: 019-30 30 00
Fax: 019-33 25 46
Web page: http://www.oru.se/Institutioner/Handelshogskolan-vid-Orebro-universitet/
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Related research

Keywords: Markov chain Monte Carlo; Structural VAR; Cointegration; Condi- tional forecasts; Time-varying parameters; Stochastic volatility; Model selection; Large VAR;

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References

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