Bayesian forecasting with highly correlated predictors

被引：10

作者：

Korobilis, Dimitris ^{[1
]}

机构：

[1] Univ Glasgow, Adam Smith Business Sch, Glasgow G12 RT, Lanark, Scotland

来源：

ECONOMICS LETTERS | 2013年 / 118卷 / 01期

关键词：

Bayesian semiparametric selection; Dirichlet process prior; Correlated predictors; Clustered coefficients; SELECTION;

D O I：

10.1016/j.econlet.2012.10.003

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms. (C) 2012 Elsevier B.V. All rights reserved.

引用

页码：148 / 150

页数：3

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