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Forecasting Industrial Production and the Early Detection of Turning Points

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  • Bruno, Giancarlo

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  • Lupi, Claudio

    ()

Abstract

In this paper we propose a simple model to forecast industrial production in Italy up to 6 months ahead. We show that the forecasts produced using the model outperform some popular forecasts as well as those stemming from an ARIMA model used as a benchmark and those from some single equation alternative models. We show how the use of these forecasts can improve the estimate of a cyclical indicator and the early detection of turning points for the manufacturing sector. This is of paramount importance for short-term economic analysis.

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File URL: http://web.unimol.it/progetti/repec/mol/ecsdps/ESDP03004.pdf
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Bibliographic Info

Paper provided by University of Molise, Dept. EGSeI in its series Economics & Statistics Discussion Papers with number esdp03004.

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Length: 36 pages
Date of creation: 14 Apr 2003
Date of revision:
Publication status: published in Empirical Economics, vol. 29, no. 3. pp. 647-671.
Handle: RePEc:mol:ecsdps:esdp03004

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Keywords: Forecasting; VAR Models; Industrial production; Cyclical indicators.;

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References

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  1. Giorgio Bodo & Roberto Golinelli & Giuseppe Parigi, 2000. "Forecasting Industrial Production in the Euro Area," Temi di discussione (Economic working papers) 370, Bank of Italy, Economic Research and International Relations Area.
  2. Giancarlo Bruno, 2001. "Seasonal Adjustment of Italian Industrial Production Index using Tramo-Seats," ISAE Working Papers 18, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
  3. Joseph Beaulieu, J. & Miron, Jeffrey A., 1993. "Seasonal unit roots in aggregate U.S. data," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 305-328.
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Citations

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Cited by:
  1. Sylvia Kaufmann, 2010. "Dating and forecasting turning points by Bayesian clustering with dynamic structure: a suggestion with an application to Austrian data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 309-344.
  2. repec:onb:oenbwp:y::i:144:b:1 is not listed on IDEAS
  3. Giancarlo Bruno, 2009. "Non-linear relation between industrial production and business surveys data," ISAE Working Papers 119, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
  4. Fichtner, Ferdinand & Rüffer, Rasmus & Schnatz, Bernd, 2009. "Leading indicators in a globalised world," Working Paper Series 1125, European Central Bank.
  5. Carmine Pappalardo & Gianfranco Piras, 2004. "Vector-Autoregression Approach to Forecast Italian Imports," ISAE Working Papers 42, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
  6. Costantini, Mauro & Pappalardo, Carmine, 2010. "A hierarchical procedure for the combination of forecasts," International Journal of Forecasting, Elsevier, vol. 26(4), pages 725-743, October.
  7. Bruno, Giancarlo & Lupi, Claudio, 2003. "Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data," MPRA Paper 42332, University Library of Munich, Germany.
  8. Giancarlo Bruno & Edoardo Otranto, 2003. "Dating the Italian Business Cycle: A Comparison of Procedures," Econometrics 0312003, EconWPA.
  9. Marco Malgarini & Patrizia Margani & Bianca Maria Martelli, 2005. "Re-engineering the ISAE manufacturing survey," ISAE Working Papers 47, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
  10. Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting monthly industrial production in real-time: from single equations to factor-based models," Empirical Economics, Springer, vol. 39(2), pages 303-336, October.
  11. Bruno, Giancarlo & Otranto, Edoardo, 2008. "Models to date the business cycle: The Italian case," Economic Modelling, Elsevier, vol. 25(5), pages 899-911, September.
  12. Charles S. Bos & Siem Jan Koopman, 2010. "Models with Time-varying Mean and Variance: A Robust Analysis of U.S. Industrial Production," Tinbergen Institute Discussion Papers 10-017/4, Tinbergen Institute.
  13. Luciana Crosilla, 2006. "The seasonality of ISAE business and consumer surveys: methodological aspects and empirical evidence," ISAE Working Papers 68, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).

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