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Energy Consumption, Survey Data and the Prediction of Industrial Production in Italy

Author

Listed:
  • Domenico J. Marchetti

    (Banca d'Italia)

  • Giuseppe Parigi

    (Banca d'Italia)

Abstract

We investigate the prediction of Italian industrial production. We first specify a model based on electricity consumption; we show that the cubic trend in such a model mostly captures the evolution over time of the electricity coefficient, which can be well approximated by a smooth transition model � la Terasvirta, with no gains in predictive power, though. We also analyze the performance of models based on data of different business surveys. According to basic statistics of forecasting accuracy, the linear energy-based model is not outperformed by any other single model, neither by a combination of forecasts. However, a more comprehensive set of evaluation criteria sheds light on the advantages of using the whole information available. Overall, the best forecasting performance is achieved by estimating a combined model which includes among regressors both energy consumption and survey data.

Suggested Citation

  • Domenico J. Marchetti & Giuseppe Parigi, 1998. "Energy Consumption, Survey Data and the Prediction of Industrial Production in Italy," Temi di discussione (Economic working papers) 342, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:wptemi:td_342_98
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    References listed on IDEAS

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    Cited by:

    1. Francesca Monti, 2008. "Forecast with judgment and models," Working Paper Research 153, National Bank of Belgium.
    2. Irving Fisher Committee, 2004. "The IFC's contribution to the 54th ISI Session, Berlin, August 2003," IFC Bulletins, Bank for International Settlements, number 17.
    3. Bilge Pekçaglayan, 2021. "Determinants of Industrial Production in Turkey: ARDL Model," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 71(71-2), pages 435-456, December.
    4. Guido Bulligan & Massimiliano Marcellino & Fabrizio Venditti, 2012. "Forecasting economic activity with higher frequency targeted predictors," Temi di discussione (Economic working papers) 847, Bank of Italy, Economic Research and International Relations Area.
    5. Bulligan, Guido & Marcellino, Massimiliano & Venditti, Fabrizio, 2015. "Forecasting economic activity with targeted predictors," International Journal of Forecasting, Elsevier, vol. 31(1), pages 188-206.
    6. Carluccio Bianchi & Alessandro Carta & Dean Fantazzini & Maria Elena De Giuli & Mario Maggi, 2010. "A copula-VAR-X approach for industrial production modelling and forecasting," Applied Economics, Taylor & Francis Journals, vol. 42(25), pages 3267-3277.

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    More about this item

    Keywords

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    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L9 - Industrial Organization - - Industry Studies: Transportation and Utilities

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