Bayesian forecast combination for VAR models

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Advances in Econometrics

ISSN: 0731-9053
Series editor(s): Thomas B. Fomby, R. Carter Hill, Ivan Jeliazkov, Juan Carlos Escanciano and Eric Hillebrand

Subject Area: Economics

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Document Information:
Title:	Bayesian forecast combination for VAR models
Author(s):	Michael K. Andersson, Sune Karlsson
Volume:	23 Editor(s): Siddhartha Chib, William Griffiths, Gary Koop, Dek Terrell ISBN: 978-1-84855-308-8 eISBN: 978-1-84855-309-5
Citation:	Michael K. Andersson, Sune Karlsson (2008), Bayesian forecast combination for VAR models, in Siddhartha Chib, William Griffiths, Gary Koop, Dek Terrell (ed.) Bayesian Econometrics (Advances in Econometrics, Volume 23), Emerald Group Publishing Limited, pp.501-524
DOI:	10.1016/S0731-9053(08)23015-X (Permanent URL)
Publisher:	Emerald Group Publishing Limited
Article type:	Chapter Item
Abstract:	We consider forecast combination and, indirectly, model selection for VAR models when there is uncertainty about which variables to include in the model in addition to the forecast variables. The key difference from traditional Bayesian variable selection is that we also allow for uncertainty regarding which endogenous variables to include in the model. That is, all models include the forecast variables, but may otherwise have differing sets of endogenous variables. This is a difficult problem to tackle with a traditional Bayesian approach. Our solution is to focus on the forecasting performance for the variables of interest and we construct model weights from the predictive likelihood of the forecast variables. The procedure is evaluated in a small simulation study and found to perform competitively in applications to real world data.