Real-time forecasting of the Australian macroeconomy using Bayesian VARs

Bo Zhang () and Bao H. Nguyen ()
Additional contact information
Bo Zhang: School of Economics, Shanghai University, https://www.shu.edu.cn/
Bao H. Nguyen: Tasmanian School of Business & Economics, University of Tasmania, https://www.utas.edu.au/profiles/staff/economics/bao-nguyen

No 2020-12, Working Papers from University of Tasmania, Tasmanian School of Business and Economics

Abstract: This paper evaluates the real-time forecast performance of alternative Bayesian Vector Autoregressive (VAR) models for the Australian macroeconomy. To this end, we construct an updated vintage database and estimate a set of model specifications with different covariance structures. The results suggest that a large VAR model with 20 variables tends to outperform a small VAR model when forecasting GDP growth, CPI inflation and unemployment rate. We find consistent evidence that the models with more flexible error covariance structures forecast GDP growth and inflation better than the standard VAR, while the standard VAR does better than its counterparts for unemployment rate. The results are robust under alternative priors and when the data includes the early stage of the COVID-19 crisis.

Keywords: Australia; real-time forecast; non-Gaussian; stochastic volatility (search for similar items in EconPapers)
JEL-codes: C11 C32 C53 C55 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2020
New Economics Papers: this item is included in nep-for, nep-mac and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published by the University of Tasmania. Discussion paper 2020-12

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