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Estimating and Forecasting GDP in Poland with Dynamic Factor Model

Author

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  • Jaroslaw Krajewski

    (Nicolaus Copernicus University in Torun)

Abstract

Presented paper concerns the dynamic factor models theory and application in the econometric analysis of GDP in Poland. DFMs are used for construction of the economic indicators and in forecasting, in analyses of the monetary policy and international business cycles. In the article we compare the forecast accuracy of DFMs with the forecast accuracy of 2 competitive models: AR model and symptomatic model. We have used 41 quarterly time series from the Polish economy. The results are encouraging. The DFM outperforms other models. The best fitted to empirical data was model with 3 factors.

Suggested Citation

  • Jaroslaw Krajewski, 2009. "Estimating and Forecasting GDP in Poland with Dynamic Factor Model," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 9, pages 139-145.
  • Handle: RePEc:cpn:umkdem:v:9:y:2009:p:139-145
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    File URL: http://www.dem.umk.pl/dem/archiwa/v9/16_JKrajewski_UMK.pdf
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    References listed on IDEAS

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    1. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    2. Jacek Kotlowski, 2008. "Forecasting inflation with dynamic factor model – the case of Poland," Working Papers 24, Department of Applied Econometrics, Warsaw School of Economics.
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    Cited by:

    1. Martin Feldkircher & Florian Huber & Josef Schreiner & Julia Woerz & Marcel Tirpak & Peter Toth, 2015. "Small-scale nowcasting models of GDP for selected CESEE countries," Working and Discussion Papers WP 4/2015, Research Department, National Bank of Slovakia.

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