Bayesian prediction with cointegrated vector autoregressions

被引:13
|
作者
Villani, M [1 ]
机构
[1] Univ Stockholm, Dept Stat, S-10691 Stockholm, Sweden
关键词
Bayesian; cointegration; inflation forecasting; model averaging; predictive density;
D O I
10.1016/S0169-2070(01)00082-6
中图分类号
F [经济];
学科分类号
02 ;
摘要
A complete procedure for calculating the joint predictive distribution of future observations based on the cointegrated vector autoregression is presented. The large degree of uncertainty in the choice of cointegration vectors is incorporated into the analysis via the prior distribution. This prior has the effect of weighing the predictive distributions based on the models with different cointegration vectors into an overall predictive distribution. The ideas of Litterman [Mimeo, Massachusetts Institute of Technology, 1980] are adopted for the prior on the short run dynamics of the process resulting in a prior which only depends on a few hyperparameters. A straightforward numerical evaluation of the predictive distribution based on Gibbs sampling is proposed. The prediction procedure is applied to a seven-variable system with a focus on forecasting Swedish inflation. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:585 / 605
页数:21
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