Abstract
In this paper we use wavelet analysis to address the problem of inflation dynamics convergence in the Euro area. The study is conducted for the 11 countries that first joined the Euro. We use a dissimilarity measure derived in the time-frequency space to estimate the degree of inflation synchronization among these countries. With this measure, we fill a dissimilarity matrix which, with multidimensional scaling, is then used to plot the different countries in a plane. Our results indicate that the degree of inflation cycles synchronization is much stronger before than after the Euro. For example, while before the Euro, Portuguese inflation is synchronized with the inflation in six other countries, after the Euro adoption any statistical evidence of synchronization disappears.
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References
Aguiar-Conraria, L., Martins, M.M., Soares, M.J.: Convergence of the economic sentiment cycles in the eurozone: A time-frequency analysis. J. Common Mark Stud. 51(3), 377–398 (2013)
Aguiar-Conraria, L., Soares, M.J.: The continuous wavelet transform: Moving beyond uni- and bivariate analysis. J. Econ. Surv. (forthcoming), http://dx.doi.org/10.1111/joes.12012
Aguiar-Conraria, L., Soares, M.J.: Business cycle synchronization and the Euro: A wavelet analysis. J. Macroecon. 33(3), 477–489 (2011)
Artis, M., Krolzig, H.M., Toro, J.: The European business cycle. Oxford Economic Papers 56(1), 1–44 (2004)
Busetti, F., Forni, L., Harvey, A., Venditti, F.: Inflation convergence and divergence within the European Monetary Union. IJCB 3(2), 95–122 (2007)
Camacho, M., Perez-Quiros, G., Saiz, L.: Are European business cycles close enough to be just one? J. Econ. Dyn. Control 30(9-10), 1687–1706 (2006)
Cavallero, A.: The convergence of inflation rates in the EU-12 area: A distribution dynamics approach. J. Macroecon. 33(2), 341–357 (2011)
Daubechies, I.: Ten Lectures on Wavelets. SIAM, Philadelphia (1992)
Foufoula-Georgiou, E., Kumar, P.: Wavelets in Geophysics. Wavelet Analysis and its Applications, vol. 4. Academic Press (1994)
Lopez, C., Papell, D.H.: Convergence of Euro area inflation rates. J. Int. Money and Financ. 31(6), 1440–1458 (2012)
Meller, B., Nautz, D.: Inflation persistence in the Euro area before and after the European Monetary Union. Econom. Model 29(4), 1170–1176 (2012)
Rouyer, T., Fromentin, J.M., Stenseth, N.C., Cazelles, B.: Analysing multiple time series and extending significance testing in wavelet analysis. Ecol. Prog. Ser. 359, 11–23 (2008)
Scharnhorst, K.: Angles in complex vector spaces. Acta Appl. Math. 69(1), 95–103 (2001)
Torrence, C., Compo, G.: A practical guide to wavelet analysis. B Am Meteorol. Soc. 79, 61–78 (1998)
Trosset, M.: Numerical algorithms for multidimensional scaling. In: Klar, R., Opitz, O. (eds.) Classification and Knowledge Organization. Studies in Classification, Data Analysis, and Knowledge Organization, pp. 80–92. Springer, Heidelberg (1997)
Zhang, Z., Moore, J.C.: Comment on “Significance tests for the wavelet power and the wavelet power spectrum” by Ge. Ann. Geophys.-Germany 30(12), 1743–1750 (2007)
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Soares, M.J., Aguiar-Conraria, L. (2014). Inflation Rate Dynamics Convergence within the Euro. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2014. ICCSA 2014. Lecture Notes in Computer Science, vol 8579. Springer, Cham. https://doi.org/10.1007/978-3-319-09144-0_10
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DOI: https://doi.org/10.1007/978-3-319-09144-0_10
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