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.

Macroeconomic forecasting in a multi-country context

Bai, Yu
;
Carriero, Andrea;Marcellino, Massimiliano
2022-01-01

Abstract

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.
2022
Bai, Yu; Carriero, Andrea; Clark, Todd E.; Marcellino, Massimiliano
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/4051972
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