Forecasting with Bayesian Vector Autoregressions
Sune Karlsson ()
No 2012:12, Working Papers from Örebro University, School of Business
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.
Keywords: Markov chain Monte Carlo; Structural VAR; Cointegration; Condi- tional forecasts; Time-varying parameters; Stochastic volatility; Model selection; Large VAR (search for similar items in EconPapers)
JEL-codes: C11 C32 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-ore
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Chapter: Forecasting with Bayesian Vector Autoregression (2013)
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Persistent link: http://EconPapers.repec.org/RePEc:hhs:oruesi:2012_012
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