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Forecasting inflation in Poland using dynamic factor model

Author

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  • Pierzak, Agnieszka

    (Ministry of Finance in Poland)

Abstract

This paper investigates the use of dynamic factor model for forecasting headline and core inflation as well as food price index in Poland. Method applied in the study extend conventional approaches by using bayesian techniques to dynamic factors' estimation, way of handling "ragged edge" data structure and allowing for the model to change over time. Forecasting results confirm that including current information extracted from data-rich environment improves inflation forecast precision and consequently DFMs perform better than the best autoregressive models. The analysis suggest also that applying dynamic model selection procedure can additionally reduce out-of-sample prediction errors.

Suggested Citation

  • Pierzak, Agnieszka, 2013. "Forecasting inflation in Poland using dynamic factor model," MF Working Papers 17, Ministry of Finance in Poland, revised 01 Aug 2013.
    • Handle: RePEc:ris:mfplwp:0017
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    dynamic factor model; forecasting; inflation; CPI;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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