Nonparametric Mixed Frequency Monitoring Macro-at-Risk

Massimiliano Marcellino and Michael Pfarrhofer

No 20442, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: We compare homoskedastic and heteroskedastic mixed frequency (MF) vector autoregression and Bayesian additive regression tree (BART) models to assess their relative performance in predicting tail risk. MF-BART is a nonlinear state space model, and we discuss linear approximation approaches to devise computationally efficient estimation algorithms. The models are applied in an out-of-sample backcasting, nowcasting and forecasting exercise for a set of quarterly and monthly macroeconomic variables in Italy. The proposed econometric refinements yield improvements in predictive accuracy.

Keywords: Mixed; frequency (search for similar items in EconPapers)
JEL-codes: C11 C22 C53 E31 E37 (search for similar items in EconPapers)
Date: 2025-07
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