IDEAS home Printed from
   My bibliography  Save this paper

Density Forecasts of Polish Industrial Production: a Probabilistic Perspective on Business Cycle Fluctuations


  • Blazej Mazur

    () (Cracow University of Economics, Poland)


Current approaches used in empirical macroeconomic analyses use the probabilistic setup and focus on evaluation of uncertainties and risks, also with respect to future business cycle fluctuations. Therefore, forecast-based business conditions indicators should be constructed using not just point forecasts, but rather density forecasts. The latter represent whole predictive distribution and provide relevant description of forecast uncertainty.We discuss a problem of model-based probabilistic inference on business cycle conditions in Poland. In particular we consider a model choice problem for density forecasts of Polish monthly industrial production index and its selected sub-indices. Based on the results we develop indicators of future economic conditions constructed using probabilistic information on future values of the index. In order to develop a relevant model class we make use of univariate Dynamic Conditional Score models with Bayesian inference methods. We assume that the conditional distribution is of the generalized t form in order to allow for heavy tails. Another group of models under consideration relies on the idea of business cycle modelling using the Flexible Fourier Form. We compare performance of alternative models based on ex-post evaluation of density forecasting accuracy using such criteria as Log-Predictive Score (LPS) and Continuous Ranked Probability Score (CRPS). The assessment of density forecasting performance for Polish industrial production index turns out to be difficult since it depends on the choice of verification window. The pre-2013 data supports the deterministic cycle model whereas more recent observations can be explained by a very simple mean-reverting Gaussian AR(4) process. This provides an indirect evidence indicating the change of pattern of Polish business cycle fluctuations after 2013. A probabilistic indicator of business conditions is also sensitive to details of its construction. The results suggest application of forecast pooling strategies as a goal for further research.

Suggested Citation

  • Blazej Mazur, 2017. "Density Forecasts of Polish Industrial Production: a Probabilistic Perspective on Business Cycle Fluctuations," Working Papers 75/2017, Institute of Economic Research, revised May 2017.
  • Handle: RePEc:pes:wpaper:2017:no75

    Download full text from publisher

    File URL:
    File Function: First version, 2017
    Download Restriction: no

    More about this item


    density forecasts; Bayesian inference; business cycle; Dynamic Conditional Score models; Generalized t distribution.;

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pes:wpaper:2017:no75. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Adam P. Balcerzak). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.