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The relationship between the PMI and the Italian index of industrial production and the impact of the latest economic crisis

Author

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  • Valentina Aprigliano

    (Universit� Libre de Bruxelles)

Abstract

Survey data attract considerable interest as timely and reliable series for assessing the state of the economy. We investigate the relationship between the manufacturing PMI and the Index of Industrial Production (IPI) for Italy, with a special focus on the effects of the latest crisis. The manufacturing PMI tracks a medium-to-long run component of the IPI quarterly growth rate, which is estimated by a one-sided multivariate Wavelet filter. This filter provides more efficient estimates at the end of the sample than the Baxter and King method. Furthermore, the Wavelet basis allows us to take into account the time-varying oscillations of a series caused by the large negative shocks characterizing the latest global crisis, while the non-parametric framework does not force us to conclude definitely for the occurrence of structural breaks not yet testable rigorously.

Suggested Citation

  • Valentina Aprigliano, 2011. "The relationship between the PMI and the Italian index of industrial production and the impact of the latest economic crisis," Temi di discussione (Economic working papers) 820, Bank of Italy, Economic Research and International Relations Area.
  • Handle: RePEc:bdi:wptemi:td_820_11
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    References listed on IDEAS

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    4. Filippo Altissimo & Antonio Bassanetti & Riccardo Cristadoro & Mario Forni & Marco Lippi & Lucrezia Reichlin & Giovanni Veronese, 2001. "A real time coincident indicator of the euro area business cycle," Temi di discussione (Economic working papers) 436, Bank of Italy, Economic Research and International Relations Area.
    5. Filippo Altissimo & Domenico J. Marchetti & Gian Paolo Oneto, 2000. "The Italian Business Cycle: Coincident and Leading Indicators and Some Stylized Facts," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 59(2), pages 147-220, September.
    6. Lippi, Marco & Reichlin, Lucrezia & Hallin, Marc & Forni, Mario & Altissimo, Filippo & Cristadoro, Riccardo & Veronese, Giovanni & Bassanetti, Antonio, 2001. "EuroCOIN: A Real Time Coincident Indicator of the Euro Area Business Cycle," CEPR Discussion Papers 3108, C.E.P.R. Discussion Papers.
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    Cited by:

    1. G. Bruno & L. Crosilla & P. Margani, 2019. "Inspecting the Relationship Between Business Confidence and Industrial Production: Evidence on Italian Survey Data," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(1), pages 1-24, April.
    2. Claire Giordano, 2020. "Goods exports and soft export indicators: is a disconnect under way?," Questioni di Economia e Finanza (Occasional Papers) 553, Bank of Italy, Economic Research and International Relations Area.
    3. Daniel Francois Meyer & Thomas Habanabakize, 2018. "Analysis of Relationships and Causality between Consumer Price Index (CPI), the Producer Price Index (PPI) and Purchasing Manager’s Index (PMI) in South Africa," Journal of Economics and Behavioral Studies, AMH International, vol. 10(6), pages 25-32.
    4. Antonio M. Conti & Concetta Rondinelli, 2015. "Easier said than done: the divergence between soft and hard data," Questioni di Economia e Finanza (Occasional Papers) 258, Bank of Italy, Economic Research and International Relations Area.

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    More about this item

    Keywords

    Wavelet analysis; principal component analysis; business cycle;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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