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Measuring the Dynamics of Global Business Cycle Connectedness

  • Francis X. Diebold

    ()

    (Department of Economics, University of Pennsylvania)

  • Kamil Yilmaz

    ()

    (Department of Economics, Koc University)

Using a connectedness-measurement technology fundamentally grounded in modern network theory, we measure real output connectedness for a set of six developed countries, 1962-2010. We show that global connectedness is sizable and time-varying over the business cycle, and we study the nature of the time variation relative to the ongoing discussion about the changing nature of the global business cycle. We also show that connectedness corresponding to transmissions to others from the United States and Japan is disproportionately important.

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File URL: http://economics.sas.upenn.edu/system/files/13-070.pdf
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Paper provided by Penn Institute for Economic Research, Department of Economics, University of Pennsylvania in its series PIER Working Paper Archive with number 13-070.

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Length: 29 pages
Date of creation: 17 Dec 2013
Date of revision:
Handle: RePEc:pen:papers:13-070
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  1. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
  2. S. Boragan Aruoba & Marco Terrones & M. Ayhan Kose & Francis X. Diebold, 2011. "Globalization, the Business Cycle, and Macroeconomic Monitoring," IMF Working Papers 11/25, International Monetary Fund.
  3. Francis X. Diebold & Kamil Yilmaz, 2008. "Measuring Financial Asset Return and Volatility Spillovers, With Application to Global Equity Markets," NBER Working Papers 13811, National Bureau of Economic Research, Inc.
  4. Margaret M. McConnell & Gabriel Perez Quiros, 1997. "Output fluctuations in the United States: what has changed since the early 1980s?," Research Paper 9735, Federal Reserve Bank of New York.
  5. Brian M. Doyle & Jon Faust, 2005. "Breaks in the Variability and Comovement of G-7 Economic Growth," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 721-740, November.
  6. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
  7. Jean-Marie Dufour & Abderrahim Taamouti, 2008. "Short and long run causality measures: theory and inference," Economics Working Papers we083720, Universidad Carlos III, Departamento de Economía.
  8. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
  9. Francis X. Diebold & Kamil Yilmaz, 2010. "Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillovers," Koç University-TUSIAD Economic Research Forum Working Papers 1001, Koc University-TUSIAD Economic Research Forum, revised Mar 2010.
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