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

Author

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  • 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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    File URL: http://www.bancaditalia.it/pubblicazioni/temi-discussione/1998/1998-0342/tema_342_98.pdf
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    References listed on IDEAS

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    1. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 119-136, Suppl. De.
    2. Bodo, Giorgio & Signorini, Luigi Federico, 1987. "Short-term forecasting of the industrial production index," International Journal of Forecasting, Elsevier, vol. 3(2), pages 245-259.
    3. Ohtani, Kazuhiro & Kakimoto, Sumio & Abe, Kenzo, 1990. "A gradual switching regression model with a flexible transition path," Economics Letters, Elsevier, vol. 32(1), pages 43-48, January.
    4. Lin, Chien-Fu Jeff & Terasvirta, Timo, 1994. "Testing the constancy of regression parameters against continuous structural change," Journal of Econometrics, Elsevier, vol. 62(2), pages 211-228, June.
    5. L. G. Godfrey & M. R. Wickens, 1981. "Testing Linear and Log-Linear Regressions for Functional Form," Review of Economic Studies, Oxford University Press, vol. 48(3), pages 487-496.
    6. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    7. Farley, John U. & Hinich, Melvin & McGuire, Timothy W., 1975. "Some comparisons of tests for a shift in the slopes of a multivariate linear time series model," Journal of Econometrics, Elsevier, vol. 3(3), pages 297-318, August.
    8. Winkler, Robert L., 1989. "Combining forecasts: A philosophical basis and some current issues," International Journal of Forecasting, Elsevier, vol. 5(4), pages 605-609.
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    Cited by:

    1. Francesca Monti, 2008. "Forecast with judgment and models," Working Paper Research 153, National Bank of Belgium.

    More about this item

    Keywords

    Italy; industrial production; energy;

    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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