Macroeconomic forecasting in a multi-country context

被引:3
|
作者
Bai, Yu [1 ]
Carriero, Andrea [2 ,3 ]
Clark, Todd E. [4 ]
Marcellino, Massimiliano [5 ,6 ]
机构
[1] Bocconi Univ, Milan, Italy
[2] Queen Mary Univ London, London, England
[3] Univ Bologna, Bologna, Italy
[4] Fed Reserve Bank Cleveland, Cleveland, OH 44114 USA
[5] Bocconi Univ, IGIER, Milan, Italy
[6] CEPR, Milan, Italy
关键词
hierarchical shrinkage; macroeconomic forecasting; multi-country VARs; scale mixtures of Normals priors; BAYESIAN VECTOR AUTOREGRESSIONS; HIERARCHICAL PRIORS; SHRINKAGE; CONVERGENCE;
D O I
10.1002/jae.2923
中图分类号
F [经济];
学科分类号
02 ;
摘要
In this paper, we propose a hierarchical shrinkage approach for multi-country VAR models. In implementation, we consider three different scale mixtures Normals priors and provide new theoretical results. Empirically, we examine how model specifications and prior choices affect the forecasting performance for GDP growth, inflation, and a short-term interest rate for the G7 economies. We find that hierarchical shrinkage, particularly as implemented with the Horseshoe prior, is very useful in forecasting inflation. It also has the best density forecast performance for output growth and the interest rate. Multi-country models generally improve on the forecast accuracy of single-country models.
引用
收藏
页码:1230 / 1255
页数:26
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