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How fused is the euro area core?: An evaluation of growth cycle co-movement and synchronization using wavelet analysis

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  • Patrick M. Crowley
  • David G. Mayes

Abstract

This paper uses several recent advances in time-varying spectral methods to analyse the growth cycles of the core of the euro area in terms of frequency content and phasing of cycles. There are two main findings. First that coherence and phasing between the three core members of the euro area (France, Germany and Italy) continue to differ, and that for France they increased in the 1990s but not noticeably since the launch of the euro. Second that similarities vary considerably according to the length of cycle. They are high for low frequencies but lower at traditional business cycle frequencies. Simply looking at business cycles loses much of the detail of the extent of co-movement in different frequency cycles within the euro area.

Suggested Citation

  • Patrick M. Crowley & David G. Mayes, 2009. "How fused is the euro area core?: An evaluation of growth cycle co-movement and synchronization using wavelet analysis," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2008(1), pages 63-95.
    • Handle: RePEc:oec:stdkab:5ksnlxp3455h
    DOI: 10.1787/jbcma-v2008-art4-en
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    Cited by:

    1. Rua, António & Nunes, Luis C., 2012. "A wavelet-based assessment of market risk: The emerging markets case," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 84-92.
    2. Verona, Fabio, 2016. "Time–frequency characterization of the U.S. financial cycle," Economics Letters, Elsevier, vol. 144(C), pages 75-79.
    3. Gallegati, Marco & Ramsey, James B., 2013. "Structural change and phase variation: A re-examination of the q-model using wavelet exploratory analysis," Structural Change and Economic Dynamics, Elsevier, vol. 25(C), pages 60-73.
    4. Aviral Tiwari & Niyati Bhanja & Arif Dar & Faridul Islam, 2015. "Time–frequency relationship between share prices and exchange rates in India: Evidence from continuous wavelets," Empirical Economics, Springer, vol. 48(2), pages 699-714, March.
    5. Monge, Manuel & Claudio-Quiroga, Gloria & Poza, Carlos, 2024. "Chinese economic behavior in times of covid-19. A new leading economic indicator based on Google trends," International Economics, Elsevier, vol. 177(C).
    6. Gallegati, Marco & Ramsey, James B., 2014. "The forward looking information content of equity and bond markets for aggregate investments," Journal of Economics and Business, Elsevier, vol. 75(C), pages 1-24.
    7. Marczak, Martyna & Gómez, Víctor, 2015. "Cyclicality of real wages in the USA and Germany: New insights from wavelet analysis," Economic Modelling, Elsevier, vol. 47(C), pages 40-52.
    8. Luís Francisco Aguiar & Pedro C. Magalhães & Maria Joana Soares, 2010. "On Waves in War and Elections Wavelet Analysis of Political Time-Series," NIPE Working Papers 1/2010, NIPE - Universidade do Minho.
    9. Angi Roesch & Harald Schmidbauer & Erhan Uluceviz, 2014. "Frequency Aspects Of Information Transmission In Networks Of Equity Markets," EcoMod2014 7200, EcoMod.
    10. Gallegati Marco & Gallegati Mauro & Ramsey James B. & Semmler Willi, 2016. "Productivity and unemployment: a scale-by-scale panel data analysis for the G7 countries," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 477-493, September.
    11. Monge, Manuel & Gil-Alana, Luis A., 2021. "Lithium industry and the U.S. crude oil prices. A fractional cointegration VAR and a Continuous Wavelet Transform analysis," Resources Policy, Elsevier, vol. 72(C).
    12. António Rua & Artur Silva Lopes, 2015. "Cohesion within the euro area and the US: A wavelet-based view," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2014(2), pages 63-76.
    13. António Rua, 2012. "Wavelets in economics," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    14. Tanveer Bagh & Abdul Waheed & Muhammad Asif Khan & Mirza Muhammad Naseer, 2023. "Effect of Economic Policy Uncertainty on China’s Stock Price Index: A Comprehensive Analysis Using Wavelet Coherence Approach," SAGE Open, , vol. 13(4), pages 21582440231, December.
    15. Esser, Andreas, 2014. "A Wavelet Approach to Synchronization of Output Cycles," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100545, Verein für Socialpolitik / German Economic Association.
    16. Andreas Brunhart, 2015. "The Swiss Business Cycle and the Lead of Small Neighbor Liechtenstein," Arbeitspapiere 51, Liechtenstein-Institut.
    17. Schmidbauer, Harald & Rösch, Angi & Uluceviz, Erhan, 2017. "Frequency aspects of information transmission in a network of three western equity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 933-946.
    18. Luís Aguiar-Conraria & Maria Soares, 2011. "Oil and the macroeconomy: using wavelets to analyze old issues," Empirical Economics, Springer, vol. 40(3), pages 645-655, May.
    19. Styliani Christodoulopoulou, 2014. "The effect of currency unions on business cycle correlations: the EMU case," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(2), pages 177-222, May.
    20. Aguiar-Conraria, LuI´s & Joana Soares, Maria, 2011. "Business cycle synchronization and the Euro: A wavelet analysis," Journal of Macroeconomics, Elsevier, vol. 33(3), pages 477-489, September.
    21. Luís Aguiar-Conraria & Pedro Brinca & Haukur Viðar Guðjónsson & Maria Joana Soares, 2015. "Optimum Currency Area and Business Cycle Synchronization Across U.S. States," NIPE Working Papers 1/2015, NIPE - Universidade do Minho.
    22. Monge, Manuel & Lazcano, Ana & Parada, José Luis, 2023. "Growth vs value investing: Persistence and time trend before and after COVID-19," Research in International Business and Finance, Elsevier, vol. 65(C).
    23. Luís Aguiar-Conraria & Teresa Maria Rodrigues & Maria Joana Soares, 2014. "Oil Shocks and the Euro as an Optimum Currency Area," Dynamic Modeling and Econometrics in Economics and Finance, in: Marco Gallegati & Willi Semmler (ed.), Wavelet Applications in Economics and Finance, edition 127, pages 143-156, Springer.
    24. Saulius Jokubaitis & Dmitrij Celov, 2022. "Business Cycle Synchronization in the EU: A Regional-Sectoral Look through Soft-Clustering and Wavelet Decomposition," Papers 2206.14128, arXiv.org.
    25. Aviral Tiwari & Niyati Bhanja & Arif Dar & Olaolu Olayeni, 2015. "Analyzing Time–Frequency Based Co-movement in Inflation: Evidence from G-7 Countries," Computational Economics, Springer;Society for Computational Economics, vol. 45(1), pages 91-109, January.

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