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Time-Varying Trend Models for Forecasting Inflation in Australia

Cross, Jamie; Zhang, Bo; Guo, Na
Working paper
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working_camp_09-2020.pdf (678.8Kb)
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https://hdl.handle.net/11250/2688909
Utgivelsesdato
2020-11-18
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  • Centre for Applied Macro- and Petroleum economics (CAMP) [99]
Sammendrag
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 can not. This includes the dramatic reduction in inflation when the RBA adopted inflation targeting, the a one-off 10 per cent Goods and Services Tax inflationary episode in 2000, and the gradually decline in inflation since 2014.
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BI Norwegian Business School
Serie
CAMP Working Paper Series;09/2020

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