Spectral Analysis of Business Cycles in the Visegrad Group Countries

• Autorzy: Arkadiusz Kijek

Warianty tytułu

Analiza spektralna cykli koniunkturalnych krajów Grupy Wyszehradzkiej

• Języki publikacji: EN

Abstrakty

EN

This paper examines the business cycle properties of Visegrad group countries. The main objective is to identify business cycles in these countries and to study the relationships between them. The author applies a modification of the Fourier analysis to estimate cycle amplitudes and frequencies. This allows for a more precise estimation of cycle characteristics than the traditional approach. The cross-spectral analysis of GDP cyclical components for the Czech Republic, Hungary, Poland and Slovakia makes it possible to assess the degree of business cycle synchronization between the countries. (original abstract)

W artykule zbadano właściwości cykli koniunkturalnych w krajach Grupy Wyszehradzkiej. Głównym celem jest identyfikacja cykli koniunkturalnych w tych państwach i analiza powiązań pomiędzy nimi. Autor wykorzystuje modyfikację transformaty Fouriera do estymacji amplitud i częstotliwości cykli. Pozwala ona na precyzyjniejsze oszacowanie charakterystyk cykli niż w tradycyjnym podejściu. Analiza cross-spektralna komponentów cyklicznych PKB dla Czech, Węgier, Polski i Słowacji umożliwiła ocenę stopnia synchronizacji cykli koniunkturalnych w tych krajach. (abstrakt oryginalny)

Słowa kluczowe

EN

Business cycles; Fourier Transform

PL

Cykl koniunkturalny; Transformacja Fouriera

• Czasopismo: Comparative Economic Research
• Rocznik: 2017
• Tom: 20
• Numer: nr 2
• Strony: 53--71

Twórcy

autor

Arkadiusz Kijek

• Maria Curie-Skłodowska University in Lublin, Poland

Bibliografia

• Aguiar-Conraria L., Soares M.J. (2011), Business Cycle Synchronization and the Euro: a Wavelet Analysis, ʻJournal of Macroeconomicsʼ, Vol. 33, 477-489.
• Artis M., Krolzig H. M., Toro J. (2004a), The European Business Cycle, ʻOxford Economic Papersʼ, 56, 1-44.
• Artis M.J., Marcellino M., Proietti T. (2004b), Characterizing the business cycle for accession countries, CEPR Discussion Papers 4457.
• Backus D.K., Kehoe P.J., Kydland F.E. (1992), International Real Business Cycles, ʻJournal of Political Economyʼ, Vol. 100, No. 4, 745-775.
• Bartlett M.S. (1950), Periodogram Analysis and Continuous Spectra, ʻBiometrikaʼ, Vol. 37, No. 1-2, 1-16.
• Baxter M., King R.G. (1995), Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series, Working Paper No. 5022, National Bureau of Economic Research, Cambridge.
• Beveridge S., Nelson C.R. (1981), A New Approach to Decomposition of Economic Time Series into Permanent and Transitory Components with Particular Attention to Measurement of the 'Business Cycle', ʻJournal of Monetary Economicsʼ, 7, 151-174.
• Burns A.F., Mitchell W.C. (1946), Measuring Business Cycles, N.Y.: National Bureau of Economic Research, New York.
• Camacho M., Perez-Quiros G., Saiz L. (2008), Do European business cycles look like one?, ʻJournal of Economic Dynamics and Controlʼ, Vol. 32, No. 7, 2165-2190.
• Campbell J.Y., Mankiw N. G. (1987), Permanent and Transitory Components in Macroeconomic Fluctuations, ʻAmerican Economic Reviewʼ (Papers and Proceedings), 77, 111-117.
• Chatfield C. (1996), The Analysis of Time Series: An Introduction, Chapman & Hall, London.
• Christiano L.J., Fitzgerald T.J. (1999), The Band Pass Filter, Working Paper No. 9906, Federal Reserve Bank of Cleveland.
• Clark P.K. (1987), The Cyclical Component of U.S. Economic Activity, ʻThe Quaterly Journal of Economicsʼ, Vol. 102, 797-814.
• Crowley P., Lee J. (2005), Decomposing the Co-movement of the Business Cycle: A Time-Frequency Analysis of Growth Cycles in the Euro Area, Bank of Finland discussion papers 12/2005.
• Darvas Z., Szapary G. (2008), Business Cycle Synchronization in the Enlarged EU, ʻOpen Economies Reviewʼ, Vol. 19, No. 1, 1-19.
• Fidrmuc J., Korhonen I. (2006), Meta-analysis of the Business Cycle Correlation Between the Euro Area and the CEECs, ʻJournal of Comparative Economicsʼ, Vol. 34, No. 3, 518-537.
• Forni M., Hallin M., Lippi M., Reichlin L. (2000), The Generalized Dynamic-factor Model: Identification and Estimation, ʻThe Review of Economics and Statisticsʼ, Vol. 82, No. 4, 540-554.
• Hamilton J.D. (1994), Time Series Analysis, Princeton University Press.
• Hanus L., Vacha L. (2015), Business Cycle Synchronization of the Visegrad Four and the European Union, IES Working Paper: 19/2015.
• Harding D., Pagan A. (2006), Synchronization of Cycles, ʻJournal of Econometricsʼ, Vol. 132, No. 1, 59-79.
• Harvey A.C. (1985), Trends and Cycles in Macroeconomic Time Series, ʻJournal of Business and Economic Statisticsʼ, Vol. 3, 216-227.
• Harvey A.C. (1989), Forecasting, Structural Time Series Models and the Kalman Filter, Cambridge University Press, Cambridge, New York and Melbourne.
• Harvey A.C. (2000), Trends Analysis, University of Cambridge, Faculty of Economics and Politics.
• Hodrick R., Prescott E. (1980), Post-War U.S. Business Cycles: An Empirical Investigation, Working paper, Carnegie Mellon University.
• Hodrick R.J., Prescott E.C. (1997), Postwar U.S. Business Cycles: An Empirical Investigation, ʻJournal of Money Credit and Bankingʼ, Vol. 29, No. 1, 1-16.
• Inotai A., Sass M. (1994), Economic Integration of Visegrad Countries. Facts and Scenarios, ʻEastern European Economicsʼ, Vol. 32, No. 6, 6-23.
• Kaposzta J., Nagy H. (2015), Status Report about the Progress of the Visegrad Countries in Relation to Europe 2020 Targets,ʻ European Spatial Research and Policyʼ, Vol. 22, No. 1, 81-99.
• Kydland F., Prescott C. (1990), Business Cycles: Real Facts and A Monetary Myth, Federal Reserve Bank of Minneapolis, Quarterly Review (Spring), 3-18.
• Lee J. (2012), Measuring Business Cycle Comovements in Europe: Evidence from a Dynamic Factor Model with Time-varying Parameters, ʻEconomics Lettersʼ, Vol. 115, No. 3, 438-440.
• Lucas R.E. (1977), Understanding Business Cycles, [in:] Brunner K., Meltzer A. H. (eds.), Stabilization of the Domestic and International Economy, Carnegie-Rochester Conference Series on Public Policy 5, Amsterdam: North Holland, 7-29.
• Nelson C.R., Plosser C.I. (1982), Trends and Random Walks in Macroeconomic Time Series: Some Evidence and Implications, ʻJournal of Monetary Economicsʼ, 10, 139-162.
• Parzen E. (1961), Mathematical considerations in the estimation of spectra: Comments on the discussion of Messers, Tukey, and Goodman, ʻechnometricsʼ, 3, 167-190; 232-234.
• Priestley M.B. (1981), Spectral Analysis and Time Series, Vols 1 and 2, Academic Press, London.
• Stock J., Watson M. (2005), Understanding Changes in International Business Cycle, ʻJournal of European Economic Associationʼ, Vol. 3, No. 5, 968-1006.
• Stock J.H., Watson M.W. (1988), Variable Trends in Economic Time Series, Journal of Economic Perspectives, Vol. 2, 147-174.
• Warner R.M. (1998), Spectral Analysis of Time Series Data, ʻThe Guilford Pressʼ, New York.
• Watson M.W. (1986), Univariate Detrending Methods with Stochastics Trends, ʻJournal of Monetary Economicsʼ, Vol. 18, No.1, 49-75.
• Zarnowitz V., Ozyildirim A. (2001), Time Series Decomposition and Measurement of Business Cycles, Trends and Growth Cycles, ʻEconomics Program Working Paper Seriesʼ, The Conference Board, New York.

Identyfikatory

DOI

https://doi.org/10.1515/cer-2017-0012