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A New Method for Combining Detrending Techniques with Application to Business Cycle Synchronization of the New EU Members

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  • Zsolt Darvas
  • Gábor Vadas

Abstract

Decomposing output into trend and cyclical components is an uncertain exercise and depends on the method applied. It is an especially dubious task for countries undergoing large structural changes, such as transition countries. Despite their deficiencies, however, univariate detrending methods are frequently adopted for both policy oriented and academic research. This paper proposes a new procedure for combining univariate detrending techniques which is based on revisions of the estimated output gaps adjusted by the variance of and the correlation among output gaps. The procedure is applied to the study of the similarity of business cycles between the euro area and new EU Member States.

Suggested Citation

  • Zsolt Darvas & Gábor Vadas, 2005. "A New Method for Combining Detrending Techniques with Application to Business Cycle Synchronization of the New EU Members," Working Papers 0505, Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest.
    • Handle: RePEc:mkg:wpaper:0505
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    References listed on IDEAS

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    1. Fidrmuc, Jarko & Korhonen, Iikka, 2006. "Meta-analysis of the business cycle correlation between the euro area and the CEECs," Journal of Comparative Economics, Elsevier, vol. 34(3), pages 518-537, September.
    2. Fidrmuc, Jarko & Korhonen, Iikka, 2004. "A meta-analysis of business cycle correlation between the euro area and CEECs : What do we know - and who cares?," BOFIT Discussion Papers 20/2004, Bank of Finland, Institute for Economies in Transition.
    3. Jarko Fidrmuc & Iikka Korhonen, 2004. "A Meta-Analysis of Business Cycle Correlations between the Euro Area, CEECs and SEECs – What Do We Know?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 76-94.
    4. András Simon & Zsolt Darvas, 2000. "Potential Output and Foreign Trade in Small Open Economies," MNB Working Papers 2000/9, Magyar Nemzeti Bank (Central Bank of Hungary).
    5. Stock, James H. & Watson, Mark W., 1999. "Business cycle fluctuations in us macroeconomic time series," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 1, pages 3-64, Elsevier.
    6. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
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    Cited by:

    1. Pierre L. Siklos & Diana N. Weymark, 2007. "Is Sterilized Intervention Effective? New International Evidence," Working Papers 142007, Hong Kong Institute for Monetary Research.
    2. Fidrmuc, Jarko & Korhonen, Iikka, 2006. "Meta-analysis of the business cycle correlation between the euro area and the CEECs," Journal of Comparative Economics, Elsevier, vol. 34(3), pages 518-537, September.
    3. Dinu. Marin & Marinas, Marius Corneliu & Socol Cristian & Socol, Aura Gabriela, 2012. "Clusterization, Persistence, Dependency and Volatility of Business Cycles in an Enlarged Euro Area," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-23, June.
    4. Dumitru, Ionut & Dumitru, Ionela, 2010. "Business Cycle Correlation of the New Meber States with Eurozone - The Case of Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 16-31, December.

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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