Bayesian forecasting with highly correlated predictors

This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that by acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms.

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Year of publication:	2012
Authors:	Korobilis, Dimitris
Institutions:	Scottish Institute for Research in Economics (SIRE)
Subject:	Bayesian semiparametric selection \| Dirichlet process prior \| correlated predictors \| clustered coefficients

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Series:	SIRE Discussion Papers.
Type of publication:	Book / Working Paper
Notes:	The text is part of a series SIRE-DP-2012-80 Number 2012-80
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011075630