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Unobserved Component Model with Observed Cycle. Use of BTS Data for Short-Term Forecasting of Industrial Production

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  • Sławomir Dudek
  • Dawid Pachucki

Abstract

In the paper we are checking the explanatory power of business tendency survey data (BTS) in short-term forecasts of industrial production within the framework of the unobserved component model (UCM). It is assumed that the "unobserved cyclical component" is common for reference quantitative variable and qualitative variable. In that sense the cyclical fluctuation of industrial production can be approximated by the fluctuations of BTS indicators. We call such a specification of structural time series model the “Unobserved component model with observed cycle" (UCM-OC). To estimate the system we are using the Kalman filter technique. Then we compare the model recursive one-period ahead forecasts to the historical path of the reference series to check its out-of-sample data fit. The forecasting properties are also evaluated against alternative models, i.e. "pure" UCM and ARIMA model. The analysis was performed for Poland and selected European Union countries.

Suggested Citation

  • Sławomir Dudek & Dawid Pachucki, 2011. "Unobserved Component Model with Observed Cycle. Use of BTS Data for Short-Term Forecasting of Industrial Production," Prace i Materiały, Instytut Rozwoju Gospodarczego (SGH), vol. 86(2), pages 83-100, January.
    • Handle: RePEc:wsd:irgpim:v:86:y:2011:i:2:p:83-100
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    References listed on IDEAS

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    1. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    2. Kuttner, Kenneth N, 1994. "Estimating Potential Output as a Latent Variable," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 361-368, July.
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