Vector Autoregression (VAR) has been a standard empirical tool used in macroeconomics and finance. In this paper we discuss how to compare alternative VAR models after they are estimated by Bayesian MCMC methods. In particular we apply a robust version of deviance information criterion (RDIC) recently developed in Li et al. (2014b) to determine the best candidate model. RDIC is a better information criterion than the widely used deviance information criterion (DIC) when latent variables are involved in candidate models. Empirical analysis using US data shows that the optimal model selected by RDIC can be different from that by DIC.
Bayes factor, DIC, VAR models, Markov Chain Monte Carlo
Essays in Honor of Peter C. B. Phillips
Chang, Yoosoon; Fomby, Thomas B.; Park, Joon Y.
City or Country
ZENG, Tao; LI, Yong; and YU, Jun.
Deviance Information Criterion for Comparing VAR Models. (2014). Essays in Honor of Peter C. B. Phillips. 33, 615-637. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/1584
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