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The United States and the Euro Area: The Role of Financial Variables

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Book cover Catching the Flu from the United States

Abstract

As we have seen before, the traditional analysis of the transmission of shocks views the trade channel as the main source of spillovers: a slowdown in the US would decrease its imports, and the associated reduction of European exports would therefore lead Europe to a period of lower growth. However, this direct trade channel can hardly account for the extent of observed spillovers, particularly as the 2007–9 global financial turmoil’s impacts on the euro area are still far from being settled. Looking at the euro area, US imports represent around 15% of the former’s exports, and the euro area exports contribute only 10% of its GDP growth. The stylised fact that the euro area lags US business cycles by a few quarters, which was discussed in detail in Chapter 2, can therefore be hardly justified, on account of rather limited trade openness.

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References

  • Ang, A., M. Piazzesi and M. Wei, 2006, ‘What Does the Yield Curve Tell Us about GDP Growth?’ Journal of Econometrics, 131, 359–403.

    Article  Google Scholar 

  • Balke, N.S., 2000, ‘Credit and Economic Activity: Credit Regimes and Nonlinear Propagation of Shocks’, Review of Economics and Statistics, 82, 344–9.

    Article  Google Scholar 

  • Bayoumi, T. and A.J. Swiston, 2007, ‘Foreign Entanglements: Estimating the Source and Size of Spillovers Across Industrial Countries’, IMF Working Paper No. 07/182.

    Google Scholar 

  • Blanchard, O. and D. Quah, 1989, ‘The Dynamic Effects of Aggregate Demand and Supply Disturbances’, American Economic Review, 79, 655–73.

    Google Scholar 

  • Bloom, N., 2009, ‘The Impact of Uncertainty Shocks’, Econometrica, 77 (3), 623–85.

    Article  Google Scholar 

  • Bloom, N., M. Floetotto and N. Jaimovich, 2009, Really Uncertain Business Cycles, Stanford University, mimeo.

    Google Scholar 

  • Boivin, J. and M. Giannoni, 2008, ‘Global Forces and Monetary Policy Effectiveness’, in J. Galí and M. Gertler (eds), International Dimensions of Monetary Policy, Chicago: University of Chicago Press, NBER Working Papers 13736.

    Google Scholar 

  • Di Mauro, F., F. Fornari and M.J. Lombardi, 2009, ‘Measuring International Spillovers’, mimeo.

    Google Scholar 

  • Diebold, F.X. and R.S. Mariano, 1995, ‘Comparing Predictive Accuracy’, Journal of Business and Economic Statistics, 13, 253–63.

    Google Scholar 

  • Diebold, F.X. and K. Yilmaz, 2009, ‘Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets’, Economic Journal, 119, 158–71.

    Article  Google Scholar 

  • Ehrmann, M., Fratzscher and R. Rigobon, 2005, ‘Stocks, Bonds, Money Markets and Exchange Rates. Measuring International Financial Transmission’, ECB Working Paper, No. 452.

    Google Scholar 

  • Espinoza, R.A., F. Fornari and M.J. Lombardi, 2009, ‘The Role of Financial Variables in Predicting Economic Activity’, ECB Working Paper No. 1108.

    Google Scholar 

  • Estrella, A., 2005, ‘Why Does the Yield Curve Predict Output and Inflation?’ Economic Journal, Royal Economic Society, 115 (505), 722–44.

    Google Scholar 

  • Estrella, A. and Mishkin, F.S., 1998, ‘Is There a Role lor Monetary Aggregates in the Conduct ol Monetary Policy?’ Journal of Monetary Economics, 40 (2), 279–304, Elsevier.

    Article  Google Scholar 

  • Estrella, A., A.P. Rodrigues and S. Schich, 2003, ‘How Stable is the Predictive Power ol the Yield Curve? Evidence from Germany and the United States’, The Review of Economics and Statistics, 85 (3), 629–44, MIT Press.

    Article  Google Scholar 

  • Fagan, G., J. Henry and R. Mestre, 2001, ‘An Area-wide Model (AWM) lor the Euro Area’, ECB Working Paper No. 42.

    Google Scholar 

  • Fornari, F. and A. Mele, 2009, ‘Financial Volatility and Economic Activity’, London School of Economics, mimeo.

    Google Scholar 

  • Fornari, F., A. Galesi and M.J. Lombardi, 2009, ‘Financial Fragility and the Business Cycle: A Nonlinear VAR Analysis’, mimeo.

    Google Scholar 

  • Fornari, F. and W. Lemke, 2009, ‘Financial Variables and Recession Probabilities’, ECB Working Paper, forthcoming.

    Google Scholar 

  • Gall, J., 1992, ‘How Well Does the Is-Lm Model Fit Postwar US Data?’ Quarterly Journal of Economics 107(2), 709–38.

    Article  Google Scholar 

  • Gerlach, S. and F. Smets, 1995, ‘The Monetary Transmission Mechanism: Evidence Irom the G7 Countries’, CEPR Discussion Paper 1219.

    Google Scholar 

  • Giacomini, R. and H. White, 2006, ‘Tests ol Conditional Predictive Ability’, Econometrica, 74, 1545–78.

    Article  Google Scholar 

  • Giannone, D., L. Reichlin and D. Small, 2005, ‘Nowcasting GDP and Inllation: The Real Time Inlormational Content ol Macroeconomic Data Releases’, CEPR Discussion Paper No. 5178.

    Google Scholar 

  • Johansen, Soren, 1988, ‘Statistical Analysis ol Cointegration Vectors’, Journal of Economic Dynamics and Control, 12 (2–3), 231–54, Elsevier.

    Article  Google Scholar 

  • Kose, M.A., C. Otrok, and C.H. Whiteman, 2003, ‘International Business Cycles: World, Region, and Country-Specilic Factors’, American Economic Review, 93, 1216–39.

    Article  Google Scholar 

  • Kose, M.A., C. Otrok, and C.H. Whiteman, 2008, ‘Understanding the Evolution ol World Business Cycles’, Journal of International Economics, 75 (1), 110–30, Elsevier.

    Article  Google Scholar 

  • Mitchell, J., 2000, ‘The Importance ol Long Run Structure lor Impulse Response Analysis in VAR Models’, NIESR Discussion Papers 172, National Institute ol Economic and Social Research.

    Google Scholar 

  • Peersman, G., 2005, ‘What Caused the Early Millennium Slowdown? Evidence Based on Vector Autoregressions’, Journal of Applied Econometrics, 20, 185–207.

    Article  Google Scholar 

  • Sims, C., 1980, ‘Macroeconomics and Reality’, Econometrica, 48, 1–48.

    Article  Google Scholar 

  • Stock, J.H. and M.W. Watson, 2003, ‘Forecasting Output and Inllation: The Role of Asset Prices’, Journal of Economic Literature, 41, 788–829.

    Article  Google Scholar 

  • Walsh, C.E., 1993, ‘What Caused the 1990–1991 Recession?’ Economic Review, Federal Reserve Bank ol San Francisco, 33–48.

    Google Scholar 

  • Yilmaz, K., 2009, ‘International Business Cycle Spillovers’, UNPUBLISHED Working Paper.

    Google Scholar 

Download references

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© 2010 Filippo di Mauro, Stephane Dees and Marco J. Lombardi

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di Mauro, F., Dees, S., Lombardi, M.J. (2010). The United States and the Euro Area: The Role of Financial Variables. In: Catching the Flu from the United States. Palgrave Macmillan, London. https://doi.org/10.1057/9780230282070_5

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