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Spillover Effects in International Business Cycles

Author

Listed:
  • Pérez-Quirós, Gabriel
  • Camacho, Máximo
  • Pacce, Matias Jose
Abstract
To analyze the international transmission of business cycle fluctuations, we propose a new multilevel dynamic factor model with a block structure that (i) does not restrict the factors to being orthogonal and (ii) mixes data sampled at quarterly and monthly frequencies. By means of Monte Carlo simulations, we show the high performance of the model in computing inferences of the unobserved factors, accounting for the spillover effects, and estimating the model's parameters. We apply our proposal to data from the G7 economies by analyzing the responses of national factors to shocks in foreign factors and by quantifying the changes in national GDP expectations in response to unexpected positive changes in foreign GDPs. Although the share of the world factor as a source of the international transmission of fluctuations is still signifi cant, this is partially absorbed by the spillover transmissions. In addition, we document a pro-cyclical channel of international transmission of output growth expectations, with the US and UK being the countries that generate the greatest spillovers and Germany and Japan being the countries that generate the smallest spillovers. Therefore, policymakers should closely monitor the evolution of foreign business cycle expectations.

Suggested Citation

  • Pérez-Quirós, Gabriel & Camacho, Máximo & Pacce, Matias Jose, 2021. "Spillover Effects in International Business Cycles," CEPR Discussion Papers 15787, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:15787
    as

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    1. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    2. S. Borağan Aruoba & Francis X. Diebold & M. Ayhan Kose & Marco E. Terrones, 2011. "Globalization, the Business Cycle, and Macroeconomic Monitoring," NBER International Seminar on Macroeconomics, University of Chicago Press, vol. 7(1), pages 245-286.
    3. Claudia Foroni & Massimiliano Marcellino, 2016. "Mixed frequency structural vector auto-regressive models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(2), pages 403-425, February.
    4. Chib, Siddhartha & Greenberg, Edward, 1994. "Bayes inference in regression models with ARMA (p, q) errors," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 183-206.
    5. 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.
    6. Duarte, Agustin & Holden, Ken, 2003. "The business cycle in the G-7 economies," International Journal of Forecasting, Elsevier, vol. 19(4), pages 685-700.
    7. Tamim Bayoumi & Andrew Swiston, 2009. "Foreign Entanglements: Estimating the Source and Size of Spillovers Across Industrial Countries," IMF Staff Papers, Palgrave Macmillan, vol. 56(2), pages 353-383, June.
    8. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
    9. Otrok, Christopher & Whiteman, Charles H, 1998. "Bayesian Leading Indicators: Measuring and Predicting Economic Conditions in Iowa," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 997-1014, November.
    10. Robert B. Litterman, 1979. "Techniques of forecasting using vector autoregressions," Working Papers 115, Federal Reserve Bank of Minneapolis.
    11. Gregory, Allan W & Head, Allen C & Raynauld, Jacques, 1997. "Measuring World Business Cycles," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(3), pages 677-701, August.
    12. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    13. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    14. Monfort, Alain & Vitale, Giovanni & Rüffer, Rasmus & Renne, Jean-Paul, 2003. "Is Economic Activity in the G7 Synchronized? Common Shocks versus Spillover Effects," CEPR Discussion Papers 4119, C.E.P.R. Discussion Papers.
    15. Haroon Mumtaz & Saverio Simonelli & Paolo Surico, 2011. "International Comovements, Business Cycle and Inflation: a Historical Perspective," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 176-198, January.
    16. Mario Crucini & Ayhan Kose & Christopher Otrok, 2011. "What are the driving forces of international business cycles?," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 156-175, January.
    17. S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions," American Economic Review, American Economic Association, vol. 100(2), pages 20-24, May.
    18. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 791-897, Elsevier.
    19. Nikolaos Antonakakis & Ioannis Chatziantoniou & George Filis, 2016. "Business Cycle Spillovers in the European Union: What is the Message Transmitted to the Core?," Manchester School, University of Manchester, vol. 84(4), pages 437-481, July.
    20. Carstensen, K. & Salzmann, L., 2017. "The G7 business cycle in a globalized world," Journal of International Money and Finance, Elsevier, vol. 73(PA), pages 134-161.
    21. Vansteenkiste, Isabel & Dées, Stéphane, 2007. "The transmission of US cyclical developments to the rest of the world," Working Paper Series 798, European Central Bank.
    22. Ms. Hélène Poirson & Mr. Sebastian Weber, 2011. "Growth Spillover Dynamics From Crisis to Recovery," IMF Working Papers 2011/218, International Monetary Fund.
    23. Bjørn Eraker & Ching Wai (Jeremy) Chiu & Andrew T. Foerster & Tae Bong Kim & Hernán D. Seoane, 2015. "Bayesian Mixed Frequency VARs," Journal of Financial Econometrics, Oxford University Press, vol. 13(3), pages 698-721.
    24. Fabian Bornhorst & Mr. Ashoka Mody, 2012. "Tests of German Resilience," IMF Working Papers 2012/239, International Monetary Fund.
    25. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, vol. 93(4), pages 1216-1239, September.
    26. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    27. Blasques, F. & Koopman, S.J. & Mallee, M. & Zhang, Z., 2016. "Weighted maximum likelihood for dynamic factor analysis and forecasting with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 405-417.
    28. Jushan Bai & Peng Wang, 2015. "Identification and Bayesian Estimation of Dynamic Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 221-240, April.
    29. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, April.
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    More about this item

    Keywords

    Spillovers; Business cycle; Mixed-frequency;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F42 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Policy Coordination and Transmission
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics

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