Bayesian testing of restrictions on vector autoregressive models |
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Authors: | Dongchu Sun Shawn Ni |
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Institution: | 1. Department of Statistics, University of Missouri, Columbia, MO 65211, USA;2. Department of Economics, University of Missouri, Columbia, MO 65211, USA;3. School of Finance and Statistics, East China Normal University, Shanghai 200241, P.R. China |
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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. |
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Keywords: | Bayesian VAR Bayes factor MCMC |
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