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Unemployment Rates Forecasts – Unobserved Component Models Versus SARIMA Models In Central And Eastern European Countries

Author

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  • Będowska-Sójka Barbara

    (Assistant Professor at the Poznan University of Economics and Business, Department of Econometrics, Poznan, Poland)

Abstract

In this paper we compare the accuracy of unemployment rates forecasts of eight Central and Eastern European countries. The unobserved component models and seasonal ARIMA models are used within a rolling short-term forecast experiment as an out-of-sample test of forecast accuracy. We find that unemployment rates present clear unconditional asymmetry in three out of eight countries. Half the cases there is no difference between forecasting accuracy of the methods used in the study. In the remaining, a proper specification of seasonal ARIMA model allows to generate better forecasts than from unobserved component models. The forecasting accuracy deteriorates in periods of rapid upward and downward movement and improves in periods of gradual change in the unemployment rates.

Suggested Citation

  • Będowska-Sójka Barbara, 2017. "Unemployment Rates Forecasts – Unobserved Component Models Versus SARIMA Models In Central And Eastern European Countries," Comparative Economic Research, Sciendo, vol. 20(2), pages 91-107, June.
    • Handle: RePEc:vrs:coecre:v:20:y:2017:i:2:p:91-107:n:6
    DOI: 10.1515/cer-2017-0014
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