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

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Author Info
Matteo Pelagatti
Valeria Negri

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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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File URL: http://www.statistica.unimib.it/utenti/WorkingPapers/WorkingPapers/20080601.pdf
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Publisher 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:
Handle: RePEc:mis:wpaper:20080601

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

Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

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References listed on IDEAS
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  1. 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. [Downloadable!] (restricted)
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    Other versions:
  3. Alessandra Iacobucci & Alain Noullez, 2005. "A Frequency Selective Filter for Short-Length Time Series," Computational Economics, Springer, vol. 25(1), pages 75-102, February. [Downloadable!] (restricted)
    Other versions:
  4. Nyblom, Jukka & Harvey, Andrew, 2000. "Tests Of Common Stochastic Trends," Econometric Theory, Cambridge University Press, vol. 16(02), pages 176-199, April. [Downloadable!]
    Other versions:
  5. Lawrence J. Christiano & Terry J. Fitzgerald, 1999. "The Band pass filter," Working Paper 9906, Federal Reserve Bank of Cleveland. [Downloadable!]
    Other versions:
    • Lawrence J. Christiano & Terry J. Fitzgerald, 1999. "The Band Pass Filter," NBER Working Papers 7257, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    • 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. [Downloadable!] (restricted)
  6. 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. [Downloadable!]
  7. Andrew C. Harvey & Thomas M. Trimbur, 2003. "General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 244-255, 03. [Downloadable!] (restricted)
    Other versions:
  8. 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. [Downloadable!] (restricted)
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