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International information flows, sentiments, and cross‐country business cycle fluctuations

Author

Listed:
  • Michał Brzoza‐Brzezina
  • Jacek Kotłowski
  • Grzegorz Wesołowski
Abstract
Business cycles are strongly correlated between countries. One possible explanation (beyond traditional economic linkages like trade or finance) is that consumer or business sentiments spread over borders and affect cyclical fluctuations in various countries. We first lend empirical support to this concept by showing that sentiments travel fast between countries, most probably directly via information flows. Then we embed this idea into a structural two‐economy new Keynesian framework where noisy information available internationally can generate cyclical fluctuations (comovement of GDP, consumption, investments, and inflation) in both countries. Estimation with US and Canadian data reveals a significant role of US noise shocks in generating common fluctuations. They explain 20%–40% of consumption variance in the US and Canada and raise the correlation between these variables by up to unity in periods of sentiment breakdowns. We also show that our estimated noise shock can be interpreted as a sentiment shock.

Suggested Citation

  • Michał Brzoza‐Brzezina & Jacek Kotłowski & Grzegorz Wesołowski, 2022. "International information flows, sentiments, and cross‐country business cycle fluctuations," Review of International Economics, Wiley Blackwell, vol. 30(4), pages 1110-1147, September.
  • Handle: RePEc:bla:reviec:v:30:y:2022:i:4:p:1110-1147
    DOI: 10.1111/roie.12597
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    References listed on IDEAS

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    1. Brzoza-Brzezina, Michał & Kotłowski, Jacek, 2020. "The Nonlinear Nature Of Country Risk And Its Implications For Dsge Models," Macroeconomic Dynamics, Cambridge University Press, vol. 24(3), pages 601-628, April.
    2. Robert C. Feenstra & Robert Inklaar & Marcel P. Timmer, 2015. "The Next Generation of the Penn World Table," American Economic Review, American Economic Association, vol. 105(10), pages 3150-3182, October.
    3. Nir Jaimovich & Sergio Rebelo, 2009. "Can News about the Future Drive the Business Cycle?," American Economic Review, American Economic Association, vol. 99(4), pages 1097-1118, September.
    4. Olivero, María Pía, 2010. "Market power in banking, countercyclical margins and the international transmission of business cycles," Journal of International Economics, Elsevier, vol. 80(2), pages 292-301, March.
    5. Paul De Grauwe & Yuemei Ji, 2017. "The International Synchronisation of Business Cycles: the Role of Animal Spirits," Open Economies Review, Springer, vol. 28(3), pages 383-412, July.
    6. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    7. Stefano Eusepi & Bruce Preston, 2011. "Expectations, Learning, and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 101(6), pages 2844-2872, October.
    8. Olivier J. Blanchard & Jean-Paul L'Huillier & Guido Lorenzoni, 2013. "News, Noise, and Fluctuations: An Empirical Exploration," American Economic Review, American Economic Association, vol. 103(7), pages 3045-3070, December.
    9. Barsky, Robert B. & Sims, Eric R., 2011. "News shocks and business cycles," Journal of Monetary Economics, Elsevier, vol. 58(3), pages 273-289.
    10. Paul Beaudry & Franck Portier, 2006. "Stock Prices, News, and Economic Fluctuations," American Economic Review, American Economic Association, vol. 96(4), pages 1293-1307, September.
    11. George‐Marios Angeletos & Fabrice Collard & Harris Dellas, 2018. "Quantifying Confidence," Econometrica, Econometric Society, vol. 86(5), pages 1689-1726, September.
    12. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    13. Harald Uhlig, 2004. "What moves GNP?," Econometric Society 2004 North American Winter Meetings 636, Econometric Society.
    14. Ryan Chahrour & Kyle Jurado, 2018. "News or Noise? The Missing Link," American Economic Review, American Economic Association, vol. 108(7), pages 1702-1736, July.
    15. Laura Nowzohour & Livio Stracca, 2020. "More Than A Feeling: Confidence, Uncertainty, And Macroeconomic Fluctuations," Journal of Economic Surveys, Wiley Blackwell, vol. 34(4), pages 691-726, September.
    16. Michał Brzoza-Brzezina & Jacek Kotłowski, 2021. "International confidence spillovers and business cycles in small open economies," Empirical Economics, Springer, vol. 61(2), pages 773-798, August.
    17. Milani, Fabio, 2017. "Sentiment and the U.S. business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 289-311.
    18. Zi‐Yi Guo, 2020. "Noisy information, risk sharing, and international business cycles," Review of International Economics, Wiley Blackwell, vol. 28(1), pages 209-234, February.
    19. Gong, Chi & Kim, Soyoung, 2018. "Regional business cycle synchronization in emerging and developing countries: Regional or global integration? Trade or financial integration?," Journal of International Money and Finance, Elsevier, vol. 84(C), pages 42-57.
    20. Frank Smets & Raf Wouters, 2003. "An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1123-1175, September.
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    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • F44 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Business Cycles

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