Ley, Eduardo and Steel, Mark F. J. (2010) Mixtures of g-priors for Bayesian model averaging with economic applications. Working Paper. Coventry: University of Warwick. Centre for Research in Statistical Methodology. Working papers, Vol.2010 (No.23).

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Abstract

We examine the issue of variable selection in linear regression
modeling, where we have a potentially large amount of possible covariates
and economic theory offers insufficient guidance on how to select the ap-
propriate subset. Bayesian Model Averaging presents a formal Bayesian
solution to dealing with model uncertainty. Our main interest here is the
effect of the prior on the results, such as posterior inclusion probabilities
of regressors and predictive performance. We combine a Binomial-Beta
prior on model size with a g-prior on the coefficients of each model. In
addition, we assign a hyperprior to g, as the choice of g has been found
to have a large impact on the results. For the prior on g, we examine
the Zellner-Siow prior and a class of Beta shrinkage priors, which covers
most choices in the recent literature. We propose a benchmark Beta prior,
inspired by earlier findings with fixed g, and show it leads to consistent
model selection. Inference is conducted through a Markov chain Monte
Carlo sampler over model space and g. We examine the performance of the
various priors in the context of simulated and real data. For the latter, we
consider two important applications in economics, namely cross-country
growth regression and returns to schooling. Recommendations to applied
users are provided.

Item Type:	Working or Discussion Paper (Working Paper)
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Regression analysis, Bayesian statistical decision theory
Series Name:	Working papers
Publisher:	University of Warwick. Centre for Research in Statistical Methodology
Place of Publication:	Coventry
Official Date:	2010
Dates:	Date Event 2010 Published
Volume:	Vol.2010
Number:	No.23
Number of Pages:	25
Institution:	University of Warwick
Status:	Not Peer Reviewed
Access rights to Published version:	Open Access

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