Year: 2025
Type: article
Abstract: ABSTRACT This paper develops a nonparametric multivariate model for assessing risks to macroecononomic outcomes in three major CESEE countries. Our model builds on Bayesian additive regression trees (BART) that remains agnostic on the relationship between the macro series and the lags thereof. Our model produces predictive distributions that exhibit non‐Gaussian features such as heavy tails, asymmetries, or multi‐modalities, making them suitable for policy analysis in extreme environments. We show that our BART model yields tail forecasts of output growth, inflation, and financial risks that are often more precise than the ones of a linear benchmark model. We then move on to analyze how the tails of selected macro series react to domestic and euro area–based financial condition shocks.
Source: Journal of Forecasting
DOI: 10.1002/for.70038
Authors: Florian Huber, Josef Schreiner
Institutions: University of Salzburg, National Bank of Austria
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,400
OpenAlex ID: W4415176231