Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/244486 
Authors: 
Year of Publication: 
2012
Series/Report no.: 
Working Paper No. 12/2012
Publisher: 
Örebro University School of Business, Örebro
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.
Subjects: 
Markov chain Monte Carlo
Structural VAR
Cointegration
Condi- tional forecasts
Time-varying parameters
Stochastic volatility
Model selection
Large VAR
JEL: 
C11
C32
C53
Document Type: 
Working Paper

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