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Forecasting Industrial Production and the Early Detection of Turning Points

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Author Info

  • Giancarlo Bruno

    (Institute for Studies and Economic Analyses)

  • Claudio Lupi

    (Institute for Studies and Economic Analyses & Libera Università Maria SS. Assunta)

Abstract

In this paper we propose a simple model to forecast industrial production in Italy. We show that the forecasts produced using the model outperform some popular forecasts as well as those stemming from a trading days- and outlier-robust ARIMA model used as a benchmark. We show that the use of appropriately selected leading variables allows to produce up to twelve-step ahead reliable forecasts. We show how and why 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://128.118.178.162/eps/em/papers/0110/0110004.pdf
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Bibliographic Info

Paper provided by EconWPA in its series Econometrics with number 0110004.

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Length: 38 pages
Date of creation: 09 Oct 2001
Date of revision:
Handle: RePEc:wpa:wuwpem:0110004

Note: Type of Document - zipped PDF; prepared on IBM PC ; pages: 38; figures: included
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Web page: http://128.118.178.162

Related research

Keywords: Forecasting; Forecast Encompassing; VAR Models; Industrial Production; Cyclical Indicators;

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References

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  1. 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).
  2. 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.
  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. Bruno, Giancarlo & Lupi, Claudio, 2003. "Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data," MPRA Paper 42332, University Library of Munich, Germany.
  2. Bruno Giancarlo & Edoardo Otranto, 2004. "Dating the Italian BUsiness Cycle: A Comparison of Procedures," ISAE Working Papers 41, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
  3. 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).
  4. 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).
  5. Francesca Monti, 2008. "Forecast with judgment and models," Working Paper Research 153, National Bank of Belgium.
  6. Carmine Pappalardo & Gianfranco Piras, 2004. "Vector-Autoregression Approach to Forecast Italian Imports," ISAE Working Papers 42, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
  7. Ferdinand Fichtner & Rasmus Rüffer & Bernd Schnatz, 2009. "Leading indicators in a globalised world," Working Paper Series 1125, European Central Bank.
  8. 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.
  9. 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.
  10. 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).
  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. Sylvia Kaufmann, 2008. "Dating and forecasting turning points by Bayesian clustering with dynamic structure: A suggestion with an application to Austrian data," Working Papers 144, Oesterreichische Nationalbank (Austrian Central Bank).

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