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A chronology of international business cycles through non-parametric decoding

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  • Hsieh Fushing
  • Shu-Chun Chen
  • Travis J. Berge
  • Òscar Jordà

Abstract

This paper introduces a new empirical strategy for the characterization of business cycles. It combines non-parametric decoding methods that classify a series into expansions and recessions but does not require specification of the underlying stochastic process generating the data. It then uses network analysis to combine the signals obtained from different economic indicators to generate a unique chronology. These methods generate a record of peak and trough dates comparable, and in one sense superior, to the NBER's own chronology. The methods are then applied to 22 OECD countries to obtain a global business cycle chronology.

Suggested Citation

  • Hsieh Fushing & Shu-Chun Chen & Travis J. Berge & Òscar Jordà, 2010. "A chronology of international business cycles through non-parametric decoding," Research Working Paper RWP 11-13, Federal Reserve Bank of Kansas City.
  • Handle: RePEc:fip:fedkrw:rwp11-13
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    References listed on IDEAS

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    1. Ambler, Steve & Cardia, Emanuela & Zimmermann, Christian, 2004. "International business cycles: What are the facts?," Journal of Monetary Economics, Elsevier, vol. 51(2), pages 257-276, March.
    2. M. Ayhan Kose & Christopher Otrok & Eswar Prasad, 2012. "Global Business Cycles: Convergence Or Decoupling?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(2), pages 511-538, May.
    3. M. Ayhan Kose & Eswar S. Prasad & Marco E. Terrones, 2003. "How Does Globalization Affect the Synchronization of Business Cycles?," American Economic Review, American Economic Association, vol. 93(2), pages 57-62, May.
    4. Stock, James H., 1987. "Measuring Business Cycle Time," Scholarly Articles 3425950, Harvard University Department of Economics.
    5. James H. Stock & Mark W. Watson, 2005. "Understanding Changes In International Business Cycle Dynamics," Journal of the European Economic Association, MIT Press, vol. 3(5), pages 968-1006, September.
    6. Ayhan Kose, M. & Otrok, Christopher & Whiteman, Charles H., 2008. "Understanding the evolution of world business cycles," Journal of International Economics, Elsevier, vol. 75(1), pages 110-130, May.
    7. Stock, James H, 1987. "Measuring Business Cycle Time," Journal of Political Economy, University of Chicago Press, vol. 95(6), pages 1240-1261, December.
    8. Klaus Nordhausen, 2009. "The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition by Trevor Hastie, Robert Tibshirani, Jerome Friedman," International Statistical Review, International Statistical Institute, vol. 77(3), pages 482-482, December.
    9. Travis Berge & Oscar Jorda, 2009. "The Classification of Economic Activity into Expansions and Recessions," Working Papers 918, University of California, Davis, Department of Economics.
    10. Hsieh Fushing & Chen Shu-Chun & Pollard Katherine, 2009. "A Nearly Exhaustive Search for CpG Islands on Whole Chromosomes," The International Journal of Biostatistics, De Gruyter, vol. 5(1), pages 1-24, May.
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    Cited by:

    1. Sergey V. Smirnov & Nikolai V. Kondrashov & Anna V. Petronevich, 2016. "Dating Cyclical Turning Points for Russia: Formal Methods and Informal Choices," HSE Working papers WP BRP 122/EC/2016, National Research University Higher School of Economics.
    2. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
    3. Travis Berge & Òscar Jordà, 2013. "A chronology of turning points in economic activity: Spain, 1850–2011," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 4(1), pages 1-34, March.
    4. Adrian Pagan, 2013. "Patterns and Their Uses," NCER Working Paper Series 96, National Centre for Econometric Research.
    5. Giusto, Andrea & Piger, Jeremy, 2017. "Identifying business cycle turning points in real time with vector quantization," International Journal of Forecasting, Elsevier, vol. 33(1), pages 174-184.

    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • F42 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Policy Coordination and Transmission

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