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Forecasting Australian Unemployment Rates using Spectral Analysis

  • Patrick J. Wilson

    ()

    (University of Technology, Sydney)

  • L.J. Perry

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.

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Article provided by Bankwest Curtin Economics Centre (BCEC), Curtin Business School in its journal Australian Journal of Labour Economics.

Volume (Year): 7 (2004)
Issue (Month): 4 (December)
Pages: 459-480

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Handle: RePEc:ozl:journl:v:7:y:2004:i:4:p:459-480
Contact details of provider: Web page: http://business.curtin.edu.au/research/publications/journals/ajle/
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  1. Max Stevenson & Maurice Peat, 2000. "Forecasting Australian Unemployment Rates," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 4(1), pages 41-55, March.
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