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Forecasting Australian Unemployment Rates using Spectral Analysis

Author

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  • Patrick J. Wilson

    (University of Technology, Sydney)

  • L.J. Perry

Abstract

Univariate spectral analysis is used to model seasonally unadjusted quarterly unemployment rate data for Australia, 1978(2) to 2002(3). Data are tested for three categories: persons, males and females. Dynamic out-of-sample forecasts are made for 8 quarters using spectral analysis models evaluated against ARIMA model counterparts. It is found that the spectral analysis models achieve higher levels of forecasting accuracy than ARIMA counterparts, including turning point forecast accuracy. These results emerge in spite of weaker in-sample explanatory power of the spectral models against the ARIMA models. It is concluded the results suggest that the spectral model is ultimately better attuned to the various cyclical forces of the past unfolding into the future.

Suggested Citation

  • Patrick J. Wilson & L.J. Perry, 2004. "Forecasting Australian Unemployment Rates using Spectral Analysis," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 7(4), pages 459-480, December.
    • Handle: RePEc:ozl:journl:v:7:y:2004:i:4:p:459-480
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    References listed on IDEAS

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    More about this item

    Keywords

    Unemployment; Models; Duration; Incidence; and Job Search Econometric and Statistical Methods; Econometric Methods: Single Equation Models; Single Variables: Time-Series Models;
    All these keywords.

    JEL classification:

    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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