Measuring the Degree of Convergence among European Business Cycles
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Abstract
The dating of a possible European business cycle has been inconclusive. At this stage, there is no consensus on the existence of such a cycle, or of its periodicity and amplitude, or of the relationship of individual member countries to that cycle. Yet cyclical convergence is the key consideration for countries that wish to be members of the currency union. The confusion over whether and to what degree the UK is converging on the cycles of its European partners, or whether its cycle is more in line with the US, is one example of this lack of consensus. Moreover, countries will vary in the components and characteristics that make up their output cycles at any moment, as well as in the state of their cycle. In this paper we show how to decompose a business cycle into a time-frequency framework. This allows us to decompose movements in output, both at the European level and in member countries, into their component cycles and allows those component cycles (and the coherence between them) to vary in their importance and cyclical characteristics. That then allows us to determine if the inconclusive convergence results obtained so far have appeared because member countries have some cycles in common, but diverge at other frequencies.
Keywords
business cycle coherence growth rates time-frequency analysisPreview
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- Agresti, A.-M. and Mojon, B. (2001). Some stylised facts on the Euro area business cycle. European Central Bank Working Paper, No 95.Google Scholar
- Altavilla, C. (2004). Do EMU members share the same business cycle? Journal of Common Market Studies, 42, 869–896.CrossRefGoogle Scholar
- Artis, M., Marcellino, M. and Priorietti, T. (2004). Dating the euro area business cycle. In L. Reichlin (ed.). The Euro Area Business Cycle: Stylised Facts and Measurement Issues, Centre for Economic Policy Research, London.Google Scholar
- Artis, M. and Zhang, W. (1997). International business cycles and the ERM: Is there a European business cycle? International Journal of Finance and Economics, 2, 1–16.CrossRefGoogle Scholar
- Artis, M. and Zhang, W. (2002). Membership of EMU: Fuzzy clustering of alternative criteria. Journal of Economic Integration, 17, 54–79.Google Scholar
- Barro, R.J. (1991). Economic growth in a cross section of countries. Quarterly Journal of Economics, 106, 407–443.CrossRefGoogle Scholar
- Barro, R.J. and Sala-I-Martin, X. (1991). Convergence across states and regions. Brookings Papers on Economic Activity, 1.Google Scholar
- Barro, R.J. and Sala-I-Martin, X. (1992). Convergence. Journal of Political Economy, 100, 223–251.CrossRefGoogle Scholar
- Baumol, W.J. (1986). Productivity growth, convergence, and welfare: What the long-run data show. American Economic Review, 76, 1072–1085.Google Scholar
- Baxter, M. and Kouparitsas, M. A. (2005). Determinants of business cycle comovement: A robust analysis. Journal of Monetary Economics 52, 113–158.CrossRefGoogle Scholar
- Blanchard, O. J. and Simon, J. (2001). The long and large decline in U.S. output volatility. Brookings Papers on Economic Activity, 1, 135–164.CrossRefGoogle Scholar
- Boashash, B. (2003). Time frequency signal analysis and processing, Elsevier, Oxford.Google Scholar
- Boashash, B. and Reilly, A. (1992). Algorithms for time-frequency signal analysis, 163–181. In B. Boashash (ed.). Time-Frequency Signal Analysis – Methods and Applications, Longman-Cheshire, Melbourne.Google Scholar
- Campbell, J.Y. and Mankiw, N.G. (1987). Permanent and transitory components in macroeconomic fluctuations. American Economic Review, 77, 111–117.Google Scholar
- Canova, F. (1998). Detrending and business cycle facts. Journal of Monetary Economics, 41, 475–512.CrossRefGoogle Scholar
- Canova, F. and Dellas, H. (1993). Trade dependence and the international business cycle. Journal of International Economics, 34, 23–47.CrossRefGoogle Scholar
- Chauvet, M. and Potter, S. (2001). Recent changes in the US business cycle: mimeo, University of California.Google Scholar
- Claasen, T.A.C.M. and Mecklenbräuker, W. F. G. (1980a). The Wigner distribution – a tool for time frequency analysis – Part I: Continuous-time signals. Philips Journal of Research, 35, 217–250.Google Scholar
- Claasen, T.A.C.M. and Mecklenbrauker, W. F. G. (1980b). The Wigner distribution – a tool for time-frequency signal analysis - Part II: Discrete-time signals. Philips Journal of Research, 35, 276–300.Google Scholar
- Claasen, T.A.C.M. and Mecklenbräuker, W.F.G. (1980c). The Wigner distribution – a tool for time frequency signal analysis - Part III: Relations with other time-frequency signal transforms. Philips Journal of Research, 35, 372–389.Google Scholar
- Clark, P.K. (1987). The cyclical component of the U.S. economic activity. Quarterly Journal of Economics, 102, 797–814.CrossRefGoogle Scholar
- Cohen, L. (1989). Time-frequency distributions – review. Institute of Electrical and Electronics Engineers (IEEE), 941–981.Google Scholar
- Demertzis, M., Hughes Hallett, A. and Rummel, O. (1998). Is a 2-Speed system in Europe the answer to the conflict between the German and the Anglo-Saxon models of monetary control? In S. Black and M. Moersch (eds). Competition and Convergence in Financial Markets – the German and Anglo-Saxon Models, Elsevier North-Holland, New York.Google Scholar
- Dowrick, S. and Nguyen, D.-T. (1989). OECD comparative economic growth 1950–1985. American Economic Review, 79, 1010–1030.Google Scholar
- Doyle, B. and Faust, J. (2003). Breaks in the variability and comovement of G7 economic growth. International Finance Discussion Paper, no 786, Board of Governors, Federal Reserve System, Washington, DC.Google Scholar
- Evans, P. and Karras, G. (1996). Convergence revisited. Journal of Monetary Economics, 37, 249–265.Google Scholar
- Forni, M. and Reichlin, L. (2001). Federal policies and local economies: Europe and the US. European Economic Review, 45, 109–134.CrossRefGoogle Scholar
- Frankel, J. and Rose, A. (1998). The endogeneity of the optimal currency area criteria. Economic Journal, 108, 1009–1025.CrossRefGoogle Scholar
- Gabor, D. (1946). Theory of communication. Journal of the Institute of Electrical Engineering, 93, 429–457.Google Scholar
- Gerdtham, U. G. and Löthgren, M. (2002). New panel results on cointegration of international health expenditure and GDP. Applied Economics, 34, 1679–1686.CrossRefGoogle Scholar
- Gerlach, S. (1989). Information, persistence, and real business cycles. Journal of Economic Dynamics and Control, 13, 187–199.CrossRefGoogle Scholar
- Gröchenig, K. (2001). Foundations of Time-Frequency Analysis. Birkhäuser, Boston.Google Scholar
- Harding, D. and Pagan, A. (2001). Extracting, analysing and using cyclical information. mimeo, Australian National University.Google Scholar
- Hughes Hallett, A. and Piscitelli, L. (2002). Does trade integration cause convergence? Economics Letters, 75, 165–170.CrossRefGoogle Scholar
- Hughes Hallett, A. and Richter, C. (2002). Are capital markets efficient? Evidence from the term structure of interest rates in Europe. Economic and Social Review, 33, 333–356.Google Scholar
- Hughes Hallett, A. and Richter, C. (2003a). Learning and monetary policy in a spectral analysis representation. In P. Wang, and S.-H. Chen (eds), Computational Intelligence in Economics and Finance, Springer Verlag, Berlin pp. 91–103.Google Scholar
- Hughes Hallett, A. and Richter, C. (2003b). A spectral analysis of the short-end of the British term structure, In R. Neck (ed.), Modelling and Control of Economic Systems, Elsevier, Amsterdam pp. 123–128.Google Scholar
- Hughes Hallett, A. and Richter, C. (2004). Spectral analysis as a tool for financial policy: An analysis of the short end of the British term structure. Computational Economics, 23, 271–288.CrossRefGoogle Scholar
- Hughes Hallett, A. and Richter, C. (2006). Is the convergence of business cycles a global or regional issue? The UK, US, and Euroland. International Journal of Finance and Economics, forthcoming.Google Scholar
- Inklaar, R. and de Haan, J. (2000). Is there really a European business cycle? CESifo Working Paper, No 268, Munich.Google Scholar
- Jenkins, G.M. and Watts, D.G. (1968). Spectral Analysis and its Applications. Holden-Day. San Francisco.Google Scholar
- Kalemli-Ozcan, S., Sorensen, B.E. and Yosha, O. (2004). Asymmetric shocks and risk sharing in a monetary union: Updated Evidence and Policy Implications for Europe. CEPR Discussion paper, no. 4463, London.Google Scholar
- Kalemli-Ozcan, S., Sorenson, B. and Yosha, O. (2001). Economic integration, industrial specialisation, and the asymmetry of macroeconomic fluctuations. Journal of International Economics, 55, 107–137.CrossRefGoogle Scholar
- Kiani, K.M. and Bidarkota, P.V. (2003). On business cycle asymmetries in G7 countries, Mimeo.Google Scholar
- Kontolemis, Z. and Samiei, H. (2000). The UK business cycle, monetary policy and EMU entry. International Monetary Fund Working Paper 00/210, Washington, D.C.Google Scholar
- LaMotte, L.R. and McWorther, A.J. (1978). An exact test for the presence of random walk coefficients in a linear regression. Journal of the American Statistical Association, 73, 816–820.CrossRefGoogle Scholar
- Laven, G. and Shi, G. (1993). Zur interpretation von Lagverteilungen. Discussion Paper, Johannes Gutenberg University, Mainz.Google Scholar
- Levy, D. and Dezhbakhsh, H. (2003). International evidence on output fluctuation and shock persistence. Journal of Monetary Economics, 50, 1499–1530.CrossRefGoogle Scholar
- Lin, Z. (1997). An introduction to time-frequency signal analysis. Sensor Review, 17, 46–53.CrossRefGoogle Scholar
- Lucas, R. E. (1988). On the mechanics of development planning. Journal of Monetary Economics, 22, 3–42.CrossRefGoogle Scholar
- Luginbuhl, R. and Koopman, S. J. (2003). Convergence in European GDP Series: A multivariate common converging trend-cycle decomposition. Tinbergen Institute Discussion Paper, 2003–031/4.Google Scholar
- Mankiw, N. G., Romer, D. and Weil, D. (1992). A contribution to the empirics of economic growth. Quarterly Journal of Economics, 107, 407–437.CrossRefGoogle Scholar
- Matz, G. and F. Hlawatsch (2003). Time-varying power spectra of nonstationary random processes. In B. Boashash (ed.), Time Frequency Signal Analysis and Processing, Elsevier, Amsterdam.Google Scholar
- McAdam, P. (2003). US, Japan and the Euro Area: Comparing business-cycle features. European Central Bank Working Paper, No 283.Google Scholar
- Nerlove, M. Grether, D.M. and Carvalho, J. L. (1995). Analysis of Economic Time Series. Academic Press. New York.Google Scholar
- Papandreou-Suppapola, A. (2002). Applications in Time-Frequency Signal Processing. CRC Press. Boca Raton.Google Scholar
- Peersman, G. and Smets, F. (2005). Industry effects of monetary policy in the Euro area. Economic Journal, 115, 319–342.CrossRefGoogle Scholar
- Ploberger, W., Kramer, W. and Kontrus, K. (1989). A new test for structural stability in the linear regression model. Journal of Econometrics, 40, 307–318.CrossRefGoogle Scholar
- Prasad, E.S. (1999). International trade and the business cycle. The Economic Journal, 109, 588–606.CrossRefGoogle Scholar
- Quah, D.T. (1993). Galton's fallacy and tests of the convergence hypothesis. Scandinavian Journal of Economics, 95, 427–443.CrossRefGoogle Scholar
- Rapach, D.E. (2002). Are real GDP levels nonstationary? Evidence from panel data tests. Southern Economic Journal, 68, 473–495.CrossRefGoogle Scholar
- Razzak, W.A. (1998). Business cycle asymmetries and the nominal exchange rate regimes. Reserve Bank of New Zealand Discussion Paper, G98/4.Google Scholar
- Romer, P.M. (1986). Increasing returns and long-run growth. Journal of Political Economy, 94, 1002–1037.CrossRefGoogle Scholar
- Rubin, J. and Thygesen, N. (1996). Monetary union and the outsiders: A cointegration, codependence analysis of the business cycles in Europe. Economic Appliquee, 44, 123–171.Google Scholar
- Sala-I-Martin, X. (1996). Regional cohesion: Evidence and theories of regional growth and convergence. European Economic Review, 40, 1325–1352.CrossRefGoogle Scholar
- Solow, R.M. (1956). A contribution to the theory of economic growth. Quarterly Journal of Economics, 70, 65–94.CrossRefGoogle Scholar
- Stock, J.H. and Watson, M. W. (2003). Understanding changes in the international business cycles. NBER Working paper, No 9859.Google Scholar
- Stock, J.H. and Watson, M. W. (2005). Understanding changes in the international business cycles dynamics. Journal of the European Economic Association, 3.Google Scholar
- Suardi, M. (2001). EMU and asymmetries in the monetary policy transmission. Economic Paper 157, European Commission, Brussels.Google Scholar
- Todd, J. (2003). Stationarity of health expenditures and GDP; Evidence from panel unit root tests with heterogeneous structural breaks. Journal of Health Economics, 22, 313–323.CrossRefPubMedGoogle Scholar
- Treasury, H.M. (2003). UK membership of the single currency: An assessment of the five economic tests, HMSO, London.Google Scholar
- U.S. Census Bureau (2002). X12-ARIMA-Reference Manual, U.S. Census Bureau, Washington, D.C.Google Scholar
- Watson, M.W. (1986). Univariate detrending methods with stochastic trends. Journal of Monetary Economics, 18, 49–75.CrossRefGoogle Scholar
- Wells, C. (1996). The Kalman Filter in Finance. Kluwer Academic Publishers. Dordrecht.Google Scholar
- Wolff, E.N. (1991). Capital formation and productivity convergence over the long term. American Economic Review, 81, 565–579.Google Scholar
- Wolters, J. (1980). Stochastic Dynamic Properties of Linear Econometric Models, Springer Verlag. Berlin.Google Scholar