Huber, Florian Koop, Gary Onorante, Luca Pfarrhofer, Michael Schreiner, Josef
Year of Publication:
ECB Working Paper No. 2510
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.
Regression tree models Bayesian macroeconomic forecasting vector autoregressions