Nowcasting in a pandemic using non-parametric mixed frequency VARs

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Huber, Florian and Koop, Gary and Onorante, Luca and Pfarrhofer, Michael and Schreiner, Josef (2023) Nowcasting in a pandemic using non-parametric mixed frequency VARs. Journal of Econometrics, 232 (1). pp. 52-69. ISSN 0304-4076 (https://doi.org/10.1016/j.jeconom.2020.11.006)

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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.

ORCID iDs

Huber, Florian, Koop, Gary ORCID logoORCID: https://orcid.org/0000-0002-6091-378X, Onorante, Luca, Pfarrhofer, Michael and Schreiner, Josef;
CORE (COnnecting REpositories)