Nowcasting in a pandemic using non-parametric mixed frequency VARs

DOI10.1016/j.jeconom.2020.11.006OpenAlexW3110070405MaRDI QIDQ2106390

Florian Huber, Gary Koop, Michael Pfarrhofer, Josef Schreiner, Luca Onorante

Publication date: 14 December 2022

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2008.12706

zbMATH Keywords

vector autoregressionsBayesianmacroeconomic forecastingregression tree models

Mathematics Subject Classification ID

Statistics (62-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)

Related Items (1)

TAIL FORECASTING WITH MULTIVARIATE BAYESIAN ADDITIVE REGRESSION TREES

Cites Work

• BART: Bayesian additive regression trees
• Variable selection for BART: an application to gene regulation
• Macroeconomics and the reality of mixed frequency data
• Variable prioritization in nonlinear black box methods: a genetic association case study
• Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors
• Real-Time Density Forecasts From Bayesian Vector Autoregressions With Stochastic Volatility
• Bayesian Approximate Kernel Regression With Variable Selection
• DATA AUGMENTATION AND DYNAMIC LINEAR MODELS
• Bayesian Regression Trees for High-Dimensional Prediction and Variable Selection
• Prediction with missing data via Bayesian Additive Regression Trees

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