Title: Bayesian testing of restrictions on vector autoregressive models
Abstract: In this study, we propose a prior on restricted Vector Autoregressive (VAR) models. The prior setting permits efficient Markov Chain Monte Carlo (MCMC) sampling from the posterior of the VAR parameters and estimation of the Bayes factor. Numerical simulations show that when the sample size is small, the Bayes factor is more effective in selecting the correct model than the commonly used Schwarz criterion. We conduct Bayesian hypothesis testing of VAR models on the macroeconomic, state-, and sector-specific effects of employment growth.
Publication Year: 2012
Publication Date: 2012-11-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 1
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