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Forecasting structural change and fat-tailed events in Australian macroeconomic variables

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  • Cross, Jamie
  • Poon, Aubrey

Abstract

The 2007/08 Global Financial Crisis has re-stimulated interest in modeling structural changes and fat tail events. In this paper, we investigate whether incorporating time variation and fat-tails into a suit of popular univariate and multivariate Gaussian distributed models can improve the forecast performance of key Australian macroeconomic variables: real GDP growth, CPI inflation and a short-term interest rate. The forecast period is from 1992Q1 to 2014Q4, thus replicating the central banks forecasting responsibilities since adopting inflation targeting. We show that time varying parameters and stochastic volatility with Student's-t error distribution are important modeling features of the data. More specifically, a vector autoregression with the proposed features provides the best interest and inflation forecasts over the entire sample. Remarkably, the full sample results show that a simple rolling window autoregressive model with Student's-t errors provides the most accurate GDP forecasts.

Suggested Citation

  • Cross, Jamie & Poon, Aubrey, 2016. "Forecasting structural change and fat-tailed events in Australian macroeconomic variables," Economic Modelling, Elsevier, vol. 58(C), pages 34-51.
  • Handle: RePEc:eee:ecmode:v:58:y:2016:i:c:p:34-51
    DOI: 10.1016/j.econmod.2016.04.021
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    More about this item

    Keywords

    Bayesian econometrics; Inflation forecasts; State space models; Stochastic volatility; Student's-t errors; Time varying parameters;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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