Publication Type
Book Chapter
Version
acceptedVersion
Publication Date
6-2014
Abstract
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.
Keywords
Bayes factor, DIC, VAR models, Markov Chain Monte Carlo
Discipline
Econometrics
Research Areas
Econometrics
Publication
Essays in Honor of Peter C. B. Phillips
Volume
33
Editor
Chang Yoosoon, Thomas B. Fomby, & Park Joon Y.
First Page
615
Last Page
637
ISBN
9781784411831
Identifier
10.1108/S0731-905320140000033017
Publisher
Emerald
City or Country
Bingley
Citation
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.
Available at: https://ink.library.smu.edu.sg/soe_research/1584
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1108/S0731-905320140000033017