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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;

Find related papers by JEL classification:

• C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
• C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
• C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

This paper has been announced in the following NEP Reports:

• NEP-ALL-2012-08-23 (All new papers)
• NEP-ECM-2012-08-23 (Econometrics)
• NEP-ETS-2012-08-23 (Econometric Time Series)
• NEP-FOR-2012-08-23 (Forecasting)
• NEP-ORE-2012-08-23 (Operations Research)

References

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

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