Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/229124
Authors: 
Huber, Florian
Koop, Gary
Onorante, Luca
Pfarrhofer, Michael
Schreiner, Josef
Year of Publication: 
2021
Series/Report no.: 
ECB Working Paper No. 2510
Abstract: 
This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using additive regression trees. We argue that regression tree models are ideally suited for macroeconomic nowcasting in the face of extreme observations, for instance those produced by the COVID-19 pandemic of 2020. This is due to their flexibility and ability to model outliers. In an application involving four major euro area countries, we find substantial improvements in nowcasting performance relative to a linear mixed frequency VAR.
Subjects: 
Regression tree models
Bayesian
macroeconomic forecasting
vector autoregressions
JEL: 
C11
C32
C53
E37
Persistent Identifier of the first edition: 
ISBN: 
978-92-899-4509-7
Document Type: 
Working Paper

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