Time-Varying Trend Models for Forecasting Inflation in Australia

27 Pages Posted: 18 Nov 2020

See all articles by Na Guo

Na Guo

School of Finance, Tianjin University of Finance and Economics, Tianjin

Bo Zhang

School of Economics, Shanghai University

Jamie Cross

Center of Applied Macroeconomics and Commodity Prices (CAMP), BI Norwegian Business School; Australian National University (ANU) - Centre for Applied Macroeconomic Analysis (CAMA)

Date Written: November 17, 2020

Abstract

We investigate whether a class of trend models with various error term structures can improve upon the forecast performance of commonly used time series models when forecasting CPI inflation in Australia. The main result is that trend models tend to provide more accurate point and density forecasts compared to conventional autoregressive and Phillips curve models. The best short-term forecasts come from a trend model with stochastic volatility in the transitory component, while medium to long-run forecasts are better made by specifying a moving average component. We also find that trend models can capture various dynamics in periods of significance which conventional models cannot. This includes the dramatic reduction in inflation when the RBA adopted inflation targeting, the one-off 10 per cent Goods and Services Tax inflationary episode in 2000, and the gradual decline in inflation since 2014.

Keywords: trend model, inflation forecast, Bayesian analysis, stochastic volatility

JEL Classification: C11, C52, E31, E37

Suggested Citation

Guo, Na and Zhang, Bo and Cross, Jamie, Time-Varying Trend Models for Forecasting Inflation in Australia (November 17, 2020). CAMA Working Paper No. 99/2020, Available at SSRN: https://ssrn.com/abstract=3731897 or http://dx.doi.org/10.2139/ssrn.3731897

Na Guo

School of Finance, Tianjin University of Finance and Economics, Tianjin ( email )

No. 25, Zhujiang Road, Hexi District
Tianjin, 300222

Bo Zhang (Contact Author)

School of Economics, Shanghai University ( email )

149 Yanchang Road
SHANGDA ROAD 99
Shanghai 200072, SHANGHAI 200444
China

Jamie Cross

Center of Applied Macroeconomics and Commodity Prices (CAMP), BI Norwegian Business School ( email )

Nydalsveien 37
Oslo, 0442
Norway

Australian National University (ANU) - Centre for Applied Macroeconomic Analysis (CAMA) ( email )

ANU College of Business and Economics
Canberra, Australian Capital Territory 0200
Australia

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