Summary
The paper proposes a set of monthly business (growth-) cycle indicators for Germany, France, Italy and the euro area useful for ex post characterization of the cycle, and, most importantly, to assess the current economic outlook. These indicators are projections of quarterly aggregates on the space spanned by a set of regressors extracted from a large panel of monthly series. Being based on static linear combinations of monthly series, they do not suffer from the end-of-sample problem associated with traditional bilateral filters (HP filter). The indicators are used to: (1) study the degree of co-movement and synchronization across economies; (2) derive a dating of the cycle; (3) obtain the ‘stylized’ cyclical facts; (4) assess the predictive content of the panel for GDP growth. The monthly indicators are good forecasters of GDP performing often better than other simple methods. As expected, since the growth cycle indicator is a ‘smoothed’ estimate of the GDP growth, the best forecasts are obtained in terms of year-on-year (rather than quarter-on-quarter) GDP growth.
The authors wish to thank Olivier de Bandt, Sandra Eickmeier, Heinz Herrmann, the discussants and the participants of the conference held in Paris for their helpful comments. Many ideas presented here were first developed in collaboration with Filippo Altissimo, Antonio Bassanetti, Mario Forni, Marco Lippi and Lucrezia Reichlin in a joint research that led to the construction of the euro area business cycle indicator Eurocoin, currently published each month by the CEPR. The usual disclaimer applies.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Altissimo, F., Bassanetti, A., Cristadoro, R., Forni, M., Lippi, M., Reichlin, L. and Veronese, G. (2001) A real time coincident indicator for the euro area business cycle, Working paper, CEPR.
Altissimo, F., Marchetti, D. and Oneto, G. (2000) The italian business cycle: Coincident and leading indicators and some stylized facts, Temi di discussione, Banca d’Italia.
Backus, D. and Kehoe, P. (1992) International evidence on the historical properties of business cycles, American Economic Review 82(4),864–888.
Baffigi, A., Golinelli, C. and Parigi, G. (2002) Euro area bridge models, Temi di discussione, Banca d’Italia.
Baxter, A. and King, R.G. (1999) Measuring business cycles approximate band-pass filters for economic time series, Review of Economics and Statistics 81(4),575–593.
Baxter, M. (1995), International Trade and Business Cycles, p.1801–1864, in Handbook of International Economics, vol.3, Grossman, G and Rogoff, K. editors, North Holland.
Bruno, G. and Otranto, E. (2004) Dating the italian business cycle: a comparison of procedures., Working Paper 41, ISAE.
Brillinger, D.R. (1981), Time Series Data Analysis and Theory, Holden Day, San Francisco.
Bry, G. and Boschan, C. (1971) Cyclical analysis of time series: Selected procedures and computer programs, Technical Working Paper 20, NBER.
Burns, A.F. and Mitchell, W.G. 1946, Measuring Business Cycles, NBER, New York.
Burnside, C. (1998) Detrending and business cycle facts: a comment, Journal of Monetary Economics 41,513–532.
Canova, F. (1994) Detrending and turning points, European Economic Review 38,614–623.
Canova, F. (1999) Does detrending matter for the determination of the reference cycle and the selection of turning points, Economic Journal 49,126–149.
Christiano, L. and Fitzgerald, J. (2003) The band pass filter, International Economic Review 44,435–465.
Cristadoro, R., Forni, M., Reichlin, L. and Veronese, G. (2005) A core inflation indicator for the euro area, Journal of Money Credit and Banking 37(3),539–560.
Croux, C.,, Forni, M. and Reichlin, L. (1998) A measure of comovement for economic variables: Theory and empirics, Review of Economics and Statistics 83(2),232–241.
Eickmeier, S. (2005) Common stationary and non-stationary factors in the euro area analyzed in large-scale factor model, mimeo, Bundesbank.
Forni, M., Hallin, M., Lippi, M. and Reichlin, L. (2005a) The generalized factor model: identification and estimation, The Review of Economics and Statistics 82, 550–554.
Forni, M., Hallin, M., Lippi, M. and Reichlin, L. (2005b) The generalized factor model: One-sided estimation and forecasting, Journal of the American Statistical Association.
Hodrick, R. and Prescott, E. (1997) Post war us business cycles: an empirical investigation, Journal of Money, Credit and Banking 29,1–16.
Kaiser, R. and Maravall, A. 2001, Measuring Business Cycles In Economic Time Series, Springer Verlag.
Kydland, F. and Prescott, E. (1982) Time to build and aggregate fluctuations, Econometrica 50,1345–1370.
Lucas, R.E. (1977) understanding Business Cycles, Carnegie-Rochester Conference Series on Public Policy 5,7–30.
Matheron, J. (2004) Business Cyle Datation in France, Germany and Italy, mimeo, Banque de France.
Monch, E. and Uhlig, H. (1999) Towards a monthly business cycle chronology for the euro area, mimeo, Humboldt University, Berlin.
Nelson, C. and Plosser, C. (1982) Trends and random walks in macroeconomic time series, Journal of Monetary Economics 10, 139–162.
Obstfeldt, M. and Rogoff, K. (2000) The six major puzzles of international macroeconomics: is there a common cause?, In: NBER Macro Annual, MIT Press
Harding, D. and Pagan, A. (2001) Rejoinder to James Hamilton, mimeo, Australian National University.
Harding, D. and Pagan, A. (2002a) Dissecting the cycle: a methodological investigation, Journal of Monetary Economics 49, 365–381.
Harding, D. and Pagan, A. (2002b) Synchronization of cycles, Working paper, Australian National University.
Monch E. and Uhlig, H. (2004), Towards a Monthly Business Cycle Chronology for the Euro Area.
Ravn, M. and Uhlig, H. (2001) On adjusting the hp-filter for the frequency of observations, Discussion Paper 40, CEPR.
Sargent, T., 1987, Macroeconomic Theory, 2nd Edition, Academic Press, London.
Stock, J. and Watson, M. (1989) New Indexes of Coincident and Leading Economic Indicators, in NBER Macroeconomics Annual.
Stock, J. and Watson, M. (1999) Business Cycle Fluctuations in U.S. Macroeconomic Time Series, Handbook ofMacroeconomics, Vol. 1A, North Holland, 3–64.
Stock, J. and Watson, M. (2002) Macroeconomic forecasting using diffusion indexes, Journal of Business and Economic Statistics 20(2), 147–162.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer Berlin · Heidelberg
About this chapter
Cite this chapter
Cristadoro, R., Veronese, G. (2006). Tracking the Economy in the Largest Euro Area Countries: a Large Datasets Approach. In: Convergence or Divergence in Europe?. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-32611-1_6
Download citation
DOI: https://doi.org/10.1007/3-540-32611-1_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32610-6
Online ISBN: 978-3-540-32611-3
eBook Packages: Business and EconomicsEconomics and Finance (R0)