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The symmetry of demand and supply shocks in the European Monetary Union

Author

Listed:
  • Henryk Bąk

    () (Warsaw School of Economics, Collegium of World Economy)

  • Sebastian Maciejewski

    () (PGE Polska Grupa Energetyczna, Risk Department)

Abstract

In this paper we apply the Blanchard and Quah (1988) SVAR methodology in order to estimate the size and frequency of demand and supply shocks for the EMU member countries in 1996−2014. Obtained SVAR estimates suggest that Eurozone’s largest economies – Germany, France and Italy – show the greatest similarity with the Eurozone under the criterion of shock correlation and amplitude. In turn, the majority of CEE countries, which are Eurozone’s latest joiners, exhibit relatively low correlations of demand and supply shocks with the euro area. The impact of the global financial crisis on the euro area’s economies is pronounced for all 16 analysed countries between 2008 Q4 and 2009 Q2. The comparison of shock correlations prior to and after the outbreak of the global financial crisis illustrates considerable changes in correlations of demand and supply shocks of individual countries with the euro area, where changes in the correlation of demand shocks are greater in magnitude, and positive changes in the correlation of demand shocks and negative changes in the correlation of supply shocks predominate.

Suggested Citation

  • Henryk Bąk & Sebastian Maciejewski, 2017. "The symmetry of demand and supply shocks in the European Monetary Union," Bank i Kredyt, Narodowy Bank Polski, vol. 48(1), pages 1-44.
  • Handle: RePEc:nbp:nbpbik:v:48:y:2017:i:1:p:1-44
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    References listed on IDEAS

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    1. Ballabriga, Fernando & Sebastian, Miguel & Valles, Javier, 1999. "European asymmetries," Journal of International Economics, Elsevier, vol. 48(2), pages 233-253, August.
    2. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    3. Karolina Konopczak & Krzysztof Marczewski, 2011. "Why so different from other CEECs – Poland’s cyclical divergence from the euro area during the recent financial crisis," Bank i Kredyt, Narodowy Bank Polski, vol. 42(2), pages 7-30.
    4. Dumitru, Ionut & Dumitru, Ionela, 2011. "Similarity of Supply and Demand Shocks Between the New Member States and the Euro Zone. The Case of Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-19, March.
    5. Michael Frenkel & Christiane Nickel, 2005. "How Symmetric are the Shocks and the Shock Adjustment Dynamics between the Euro Area and Central and Eastern European Countries?," Journal of Common Market Studies, Wiley Blackwell, vol. 43(1), pages 53-74, March.
    6. Domenico Giannone & Michele Lenza & Lucrezia Reichlin, 2010. "Business Cycles in the Euro Area," NBER Chapters,in: Europe and the Euro, pages 141-167 National Bureau of Economic Research, Inc.
    7. Bernard Fingleton & Harry Garretsen & Ron Martin, 2015. "Shocking aspects of monetary union: the vulnerability of regions in Euroland," Journal of Economic Geography, Oxford University Press, vol. 15(5), pages 907-934.
    8. Sebnem Kalemli-Ozcan & Bent E. Sorensen & Oved Yosha, 2004. "Asymmetric Shocks and Risk Sharing in a Monetary Union: Updated Evidence and Policy Implications for Europe," Working Papers 2004-05, Department of Economics, University of Houston.
    9. Fidrmuc, Jarko & Korhonen, Iikka, 2001. "Similarity of supply and demand shocks between the euro area and the accession countries," BOFIT Discussion Papers 14/2001, Bank of Finland, Institute for Economies in Transition.
    10. Giannone, Domenico & Reichlin, Lucrezia & Lenza, Michele, 2009. "Business cycles in the euro area," Working Paper Series 1010, European Central Bank.
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    More about this item

    Keywords

    time series models; asymmetric shocks; the euro area;

    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
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • F44 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Business Cycles

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