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Forecasting industrial production in the Euro area

Author

Listed:
  • Giuseppe Parigi

    () (Research Department, Bank of Italy, Via Nazionale 91, 00184 Roma, Italy)

  • Roberto Golinelli

    () (Department of Economics, Strada Maggiore 45, 40125 - Bologna, Italy http://www.spbo.unibo.it/pais/golinelli/)

  • Giorgio Bodo

    () (Group Treasurer Fiat Spa, Via Nizza 250, 10126 Torino, Italy)

Abstract

The creation of the Euro area has increased the importance of obtaining timely information about short-term changes in the area's real activity. In this paper we propose a number of alternative short term forecasting models, ranging from simple ARIMA models to more complex cointegrated VAR and conditional models, to forecast the index of industrial production in the euro area. A conditional error-correction model in which the aggregate index of industrial production for the area is explained by the US industrial production index and the business confidence index from the European Commission harmonised survey on manufacturing firms achieves the best score in terms of forecasting capacity.

Suggested Citation

  • Giuseppe Parigi & Roberto Golinelli & Giorgio Bodo, 2000. "Forecasting industrial production in the Euro area," Empirical Economics, Springer, vol. 25(4), pages 541-561.
  • Handle: RePEc:spr:empeco:v:25:y:2000:i:4:p:541-561 Note: received: Jan. 2000/Final version received: March 2000
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    References listed on IDEAS

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    1. Baffigi, A. & Pagnini, M. & Quintiliani, F., 1999. "Industrial Districts and Local Banks: Do the Twins Ever Meet?," Papers 347, Banca Italia - Servizio di Studi.
    2. Osterwald-Lenum, Michael, 1992. "A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 461-472, August.
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    Cited by:

    1. Giancarlo Bruno & Claudio Lupi, 2004. "Forecasting industrial production and the early detection of turning points," Empirical Economics, Springer, pages 647-671.
    2. Hwee Kwan Chow & Keen Meng Choy, 2004. "Forecasting the Global Electronics Cycle with Leading Indicators: A VAR Approach," Departmental Working Papers wp0407, National University of Singapore, Department of Economics.
    3. Karl Taylor & Robert McNabb, 2007. "Business Cycles and the Role of Confidence: Evidence for Europe," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, pages 185-208.
    4. Alberto Baffigi & Roberto Golinelli & Giuseppe Parigi, 2002. "Real-time GDP forecasting in the euro area," Temi di discussione (Economic working papers) 456, Bank of Italy, Economic Research and International Relations Area.
    5. Golinelli, Roberto & Parigi, Giuseppe, 2014. "Tracking world trade and GDP in real time," International Journal of Forecasting, Elsevier, vol. 30(4), pages 847-862.
    6. Anna Sophia Ciesielski & Klaus Wohlrabe, 2011. "Sektorale Prognosen im Verarbeitenden Gewerbe," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 64(22), pages 27-35, November.
    7. Alessandro Girardi & Roberto Golinelli & Carmine Pappalardo, 2017. "The role of indicator selection in nowcasting euro-area GDP in pseudo-real time," Empirical Economics, Springer, pages 79-99.
    8. Konstantinou, Panagiotis & Tagkalakis, Athanasios, 2011. "Boosting confidence: Is there a role for fiscal policy?," Economic Modelling, Elsevier, vol. 28(4), pages 1629-1641, July.
    9. Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting industrial production: the role of information and methods," IFC Bulletins chapters,in: Bank for International Settlements (ed.), The IFC's contribution to the 57th ISI Session, Durban, August 2009, volume 33, pages 227-235 Bank for International Settlements.
    10. 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.
    11. Chow, Hwee Kwan & Choy, Keen Meng, 2006. "Forecasting the global electronics cycle with leading indicators: A Bayesian VAR approach," International Journal of Forecasting, Elsevier, vol. 22(2), pages 301-315.
    12. Kevin Moran & Simplice Aime Nono, 2016. "Using Confidence Data to Forecast the Canadian Business Cycle," Cahiers de recherche 1606, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    13. Claveria, Oscar & Pons, Ernest & Ramos, Raul, 2007. "Business and consumer expectations and macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 47-69.
    14. Bruno, Giancarlo & Lupi, Claudio, 2003. "Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data," MPRA Paper 42332, University Library of Munich, Germany.
    15. Carstensen Kai & Wohlrabe Klaus & Ziegler Christina, 2011. "Predictive Ability of Business Cycle Indicators under Test: A Case Study for the Euro Area Industrial Production," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 82-106, February.
    16. Robert Lehmann & Klaus Wohlrabe, 2015. "Forecasting GDP at the Regional Level with Many Predictors," German Economic Review, Verein für Socialpolitik, vol. 16(2), pages 226-254, May.
    17. 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.
    18. Ece Oral & Dilara Ece & Turknur Hamsici, 2005. "Building Up a Real Sector Business Confidence Index for Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 5(1), pages 23-54.
    19. Baffigi, Alberto & Golinelli, Roberto & Parigi, Giuseppe, 2004. "Bridge models to forecast the euro area GDP," International Journal of Forecasting, Elsevier, vol. 20(3), pages 447-460.
    20. Rünstler, Gerhard & Sédillot, Franck, 2003. "Short-term estimates of euro area real GDP by means of monthly data," Working Paper Series 276, European Central Bank.

    More about this item

    Keywords

    Forecasts comparison · alternative models · conditional ECM;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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