Bayesian forecasting with highly correlated predictors

Dimitris Korobilis

No 2012-80, SIRE Discussion Papers from Scottish Institute for Research in Economics (SIRE)

Abstract: 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.

Keywords: Bayesian semiparametric selection; Dirichlet process prior; correlated predictors; clustered coefficients (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Bayesian forecasting with highly correlated predictors (2013)
Working Paper: Bayesian forecasting with highly correlated predictors (2012)
Working Paper: Bayesian Forecasting with Highly Correlated Predictors (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:edn:sirdps:415

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