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Milan’s Cycle as an Accurate Leading Indicator for the Italian Business Cycle

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  • Matteo Pelagatti
  • Valeria Negri

Abstract

A coincident business cycle indicator for the Milan area is built on the basis of a monthly industrial survey carried out by Assolombarda, the largest territorial entrepreneurial association in Italy. The indicator is extracted from three time series concerning the production level and the internal and foreign order book as declared by some 250 Assolombarda associates. This indicator is potentially very valuable in itself, being Milan one of the most dynamic economic systems in Italy and Europe, but it becomes much more interesting when compared to the Italian business cycle as extracted form the Italian industrial production index. Indeed, notwithstanding the deep differences in the nature of the data, the indicator for Milan has an extremely high coherence with the Italian cycle and the former leads the latter by approximately 4-5 months. Furthermore there is a direct relation between the amplitude of the cycle and the leading time of the Milan indicator.

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Bibliographic Info

Paper provided by Università degli Studi di Milano-Bicocca, Dipartimento di Statistica in its series Working Papers with number 20080601.

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Length: 10 pages
Date of creation: May 2008
Date of revision:
Publication status: Published in OECD Journal: Journal of Business Cycle Measurement and Analysis, 2010, vol. 2010, no. 2. artilce 2.
Handle: RePEc:mis:wpaper:20080601

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Web page: http://www.statistica.unimib.it
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Keywords: Leading indicator; unobserved components model; structural time series model; local business survey;

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  1. Matteo Pelagatti, 2003. "Duration Dependent Markov-Switching Vector Autoregression: Properties, Bayesian Inference, Software and Application," Working Papers 20051101, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica, revised Nov 2005.
  2. Alessandra Iacobucci & Alain Noullez, 2004. "A Frequency Selective Filter for Short-Length Time Series," Documents de Travail de l'OFCE 2004-05, Observatoire Francais des Conjonctures Economiques (OFCE).
  3. Lawrence J. Christiano & Terry J. Fitzgerald, 1999. "The Band pass filter," Working Paper 9906, Federal Reserve Bank of Cleveland.
    • Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, 05.
  4. Nyblom, Jukka & Harvey, Andrew, 1999. "Tests of Common Stochastic Trends," Cambridge Working Papers in Economics 9902, Faculty of Economics, University of Cambridge.
  5. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
  6. Carvalho, Vasco & Harvey, Andrew & Trimbur, Thomas, 2007. "A Note on Common Cycles, Common Trends, and Convergence," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 12-20, January.
  7. Harvey, A.C. & Trimbur, T.M., 2001. "General Model-based Filters for Extracting Cycles and Trends in Economic Time Series," Cambridge Working Papers in Economics 0113, Faculty of Economics, University of Cambridge.
  8. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
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