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How have global shocks impacted the real effective exchange rates of individual Euro area countries since the Euro's creation?

Author

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  • Matthieu Bussiere
  • Alexander Chudik
  • Arnaud Mehl

Abstract

This paper uncovers the response pattern to global shocks of euro area countries' real effective exchange rates before and after the start of Economic and Monetary Union (EMU), a largely open ended question when the euro was created. We apply to that end a newly developed methodology based on high dimensional VAR theory. This approach features a dominant unit to a large set of over 60 countries' real effective exchange rates and is based on the comparison of two estimated systems: one before and one after EMU. ; We find strong evidence that the pattern of responses depends crucially on the nature of global shocks. In particular, post-EMU responses to global US dollar shocks have become similar to Germany's response before EMU, i.e. to that of the economy that used to issue Europe's most credible legacy currency. ; By contrast, post-EMU responses of euro area countries to global risk aversion shocks have become similar to those of Italy, Portugal or Spain before EMU, i.e. of economies of the euro area's periphery. Our findings also suggest that the divergence in external competitiveness among euro area countries over the last decade, which is at the core of today's debate on the future of the euro area, is more likely due to country-specific shocks than to global shocks.

Suggested Citation

  • Matthieu Bussiere & Alexander Chudik & Arnaud Mehl, 2011. "How have global shocks impacted the real effective exchange rates of individual Euro area countries since the Euro's creation?," Globalization Institute Working Papers 102, Federal Reserve Bank of Dallas.
  • Handle: RePEc:fip:feddgw:102
    Note: Published as: Bussiere, Matthieu, Alexander Chudik and Arnaud Mehl (2013), "How Have Global Shocks Impacted the Real Effective Exchange Rates of Individual Euro Area Countries Since the Euro's Creation?" The B.E. Journal of Macroeconomics 13 (1): 1-48.
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    2. Alexander Chudik & M. Hashem Pesaran, 2016. "Theory And Practice Of Gvar Modelling," Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 165-197, February.
    3. Shiyun Cao & Qiankun Zhou, 2022. "Common Correlated Effects Estimation for Dynamic Heterogeneous Panels with Non-Stationary Multi-Factor Error Structures," Econometrics, MDPI, vol. 10(3), pages 1-27, August.
    4. Michaelides, Panayotis G. & Tsionas, Efthymios G. & Konstantakis, Konstantinos N., 2018. "Debt Crisis in Europe (2001-2015): A Network General Equilibrium GVAR approach," MPRA Paper 89998, University Library of Munich, Germany.
    5. Filippo di Mauro & Alexander Al-Haschimi & Stephane Dees & Martina Jancokova, 2014. "Linking Distress of Financial Institutions to Macrofinancial Shocks," EcoMod2014 6807, EcoMod.
    6. Alexander Chudik & M. Hashem Pesaran, 2013. "Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 592-649, August.
    7. Konstantinos N. Konstantakis & Panayotis G. Michaelides & Livia Chatzieleftheriou & Arsenios‐Georgios N. Prelorentzos, 2022. "Crisis and the Chinese miracle: A network—GVAR model," Bulletin of Economic Research, Wiley Blackwell, vol. 74(3), pages 900-921, July.
    8. Huidan Xue & Chenguang Li & Liming Wang & Wen-Hao Su, 2021. "Spatial Price Transmission and Price Dynamics of Global Butter Export Market under Economic Shocks," Sustainability, MDPI, vol. 13(16), pages 1-24, August.
    9. Szczypińska, Agnieszka, 2014. "Does the halo effect still hold? The (post-) crisis perspective for the euro candidates," MF Working Papers 18, Ministry of Finance in Poland, revised 30 Jan 2014.
    10. Tsionas, Efthymios G. & Konstantakis, Konstantinos N. & Michaelides, Panayotis G., 2016. "Bayesian GVAR with k-endogenous dominants & input–output weights: Financial and trade channels in crisis transmission for BRICs," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 42(C), pages 1-26.
    11. Alexander Chudik, 2014. "Toward a Better Understanding of Macroeconomic Interdependence," Annual Report, Globalization and Monetary Policy Institute, Federal Reserve Bank of Dallas, pages 16-21.

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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