Statistical analysis of business cycle fluctuations in Poland before and after the crisis


  • Łukasz Lenart Cracow University of Economics
  • Błażej Mazur Cracow University of Economics
  • Mateusz Pipień Cracow University of Economics



APC processes, subsampling, Bayesian inference, global economic crisis, business cycle fluctuations


The main objective of the paper is to investigate properties of business cycles in the Polish economy before and after the recent crisis. The essential issue addressed here is whether there is statistical evidence that the recent crisis has affected the properties of the business cycle fluctuations. In order to improve robustness of the results, we do not confine ourselves to any single inference method, but instead use different groups of statistical tools, including non-parametric methods based on subsampling and parametric Bayesian methods. We examine monthly series of industrial production (from January 1995 till December 2014), considering the properties of cycles in growth rates and in deviations from long-run trend. Empirical analysis is based on the sequence of expanding-window samples, with the shortest sample ending in December 2006. The main finding is that the two frequencies driving business cycle fluctuations in Poland correspond to cycles with periods of 2 and 3.5 years, and (perhaps surprisingly) the result holds both before and after the crisis. We, therefore, find no support for the claim that features (in particular frequencies) that characterize Polish business cycle fluctuations have changed after the recent crisis. The conclusion is unanimously supported by various statistical methods that are used in the paper, however, it is based on relatively short series of the data currently available.


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Adamowicz, E., Dudek, S., Pachucki, D., & Walczyk, W. (2008). Synchronizacja cyklu koniunkturalnego polskiej gospodarki z krajami strefy euro w kontekście struktury tych gospodarek. Instytut Rozwoju Gospodarczego Szkoły Głównej Handlowej. Retrieved from /NBP/Publikacje/analityczne/irg_sghP.pdf (02.02.2015).
Blanchard, O., & Simon, J. (2001). The Long and Large Decline in U.S. Output Volatility. Brookings Papers on Economic Activity, 32(1). DOI:
Borio, C. (2014). The Financial Cycle and Macroeconomics: What Have We Learnt? Journal of Banking & Finance. 45. DOI: jbankfin.2013.07.031.
Borio, C., McCauley, R., & McGuire, P. (2011). Global Credit and Domestic Credit Booms. BIS Quarterly Review. Retrieved from qtrpdf/r_qt1109f.pdf (01.02.2015).
Corduneanu, C. (1989). Almost Periodic Functions. New York: Chelsea.
Doyle, B., & Faust, J. (2005). Breaks in the Variability and Comovement of G?7 Economic Growth. Review of Economics and Statistics, 87(4). DOI:
Drehmann, M., Borio, C., & Tsatsaronis, K. (2012). Characterising the Financial Cycle: Don?t Lose Sight of the Medium Term!. BIS Working Papers, 380. Retrieved from (01.02.2015).
Gradzewicz, M., Growiec, J., Hagemejer, J., & Popowski, P. (2010). Cykl koniunkturalny w Polsce ? wnioski z analizy spektralnej. Bank i Kredyt, 41(5).
Imbs, J. (2004). Trade, Finance, Specialization, and Synchronization. Review of Economics and Statistics, 86(3). DOI: 11707.
Kannan, P., Scott, A., & Terrones, M. A. (2012). From Recession to Recovery: How Soon and How Strong. In Proceedings of the Conference Financial Crises: Causes, Consequences and Policy Responses. IMF. Retrieved from (01.02.2015).
Kose, M. A., Otrok, C., & Whiteman, C. (2008). Understanding the Evolution of World Business Cycles. Journal of International Economics, 75(1). DOI:
Kose, M. A., Prasad, E., & Terrones, M. (2003). How Does Globalization Affect the Synchronization of Business Cycles? American Economic Review, 93(2). DOI:
Lenart, Ł. (2013). Non?parametric Frequency Identification and Sstimation in Mean Function for Almost Periodically Correlated Time Series. Journal of Multivariate Analysis, 115. DOI:
Lenart, Ł., & Pipień, M. (2013). Almost Periodically Correlated Time Series in Business Fluctuations Analysis. Acta Physica Polonica A, 123(3). DOI:
Li, T., & Song, K. (2002). Asymptotic Analysis of a Fast Algorithm for Efficient Multiple Frequency Estimation. IEEE Transactions on Information Theory, 48(10). DOI: 10.1109/TIT.2002.802635.
Politis, D., Romano, J., & Wolf, M. (1999). Subsampling. New York: Springer?Verlag. DOI:
Romer, Ch. (1999). Changes in Business Cycles: Evidence and Explanations. Journal of Economic Perspective, 13(2). DOI: 13.2.23.
Skrzypczyńska, M. (2014). Cyclical Processes in the Polish Economy. Central European Journal of Economic Modelling and Econometrics, 6(3).
Skrzypczyński, P. (2010). Metody spektralne w analizie cyklu koniunkturalnego gospodarki polskiej. Materiały i Studia, 252.
Stock, J. H., & Watson, M. W. (2003). Has the Business Cycle Changed and Why. NBER Macroeconomics Annual, 17. DOI: 5284.
Stock, J., & Watson, M. (2005). Understanding Changes in International Business Cycle Dynamics. Journal of the European Economic Association, 3(5). DOI:
Taylor, J. B. (1998). Monetary Policy and the Long Boom. Federal Reserve Bank of St. Louis Review, November/December. Retrieved from (04.02.2015).
Woodford, M. (2003). Interest and Prices: Foundations of a Theory of Monetary Policy. Princeton: Princeton University Press. DOI: 1017/S1365100505040253.
Wośko, Z. (2009). Czy filtry liniowe są przydatnym narzędziem badania koniunktury? Analiza spektralna na przykładzie ankietowych wskaźników koniunktury. In J. Czech-Rogosz, J. Pietrucha & R. Żelazny (Eds.). Koniunktura gospodarcza: od bańki internetowej do kryzysu subprime. Warszawa: C.H.BECK.




How to Cite

Lenart, Łukasz, Mazur, B., & Pipień, M. (2016). Statistical analysis of business cycle fluctuations in Poland before and after the crisis. Equilibrium. Quarterly Journal of Economics and Economic Policy, 11(4), 769–783.



Monetary policy and business cycle

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