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Short-term forecasting of GDP using large datasets: a pseudo real-time forecast evaluation exercise

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Author Info

  • G. Rünstler

    (European Central Bank, Frankfurt|Main, Germany)

  • K. Barhoumi

    (Banque de France, Paris, France)

  • S. Benk

    (Magyar Nemzeti Bank, Budapest, Hungary)

  • R. Cristadoro

    (Banca d'Italia, Rome, Italy)

  • A. Den Reijer

    (Sveriges Riksbank, Stockholm, Sweden)

  • A. Jakaitiene

    (Institute of Mathematics and Informatics, Vilnius, Lithuania)

  • P. Jelonek

    (Narodowy Bank Polski, Warsaw, Poland)

  • A. Rua

    (Banco de Portugal, Lisbon, Portugal)

  • K. Ruth

    (Deutsche Bundesbank, Frankfurt, Germany)

  • C. Van Nieuwenhuyze

    (National Bank of Belgium, Brussels, Belgium)

Abstract

This paper performs a large-scale forecast evaluation exercise to assess the performance of different models for the short-term forecasting of GDP, resorting to large datasets from ten European countries. Several versions of factor models are considered and cross-country evidence is provided. The forecasting exercise is performed in a simulated real-time context, which takes account of publication lags in the individual series. In general, we find that factor models perform best and models that exploit monthly information outperform models that use purely quarterly data. However, the improvement over the simpler, quarterly models remains contained. Copyright © 2009 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1105
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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 28 (2009)
Issue (Month): 7 ()
Pages: 595-611

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Handle: RePEc:jof:jforec:v:28:y:2009:i:7:p:595-611

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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Cited by:
  1. Paulo Soares Esteves & António Rua, 2012. "Short-term forecasting for the portuguese economy: a methodological overview," Economic Bulletin and Financial Stability Report Articles, Banco de Portugal, Economics and Research Department.
  2. Van Beveren, Ilke & Bernard, Andrew B & Blanchard, Emily J & Vandenbussche, Hylke, 2011. "Carry-along trade," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/387875, Katholieke Universiteit Leuven.
  3. Bernard, Andrew B & Van Beveren, Ilke & Vandenbussche, Hylke, 2010. "Multi-product exporters, carry-along trade and the margins of trade," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/386402, Katholieke Universiteit Leuven.
  4. Bhattacharya, Rudrani & Pandey, Radhika & Veronese, Giovanni, 2011. "Tracking India Growth in Real Time," Working Papers 11/90, National Institute of Public Finance and Policy.
  5. 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.
  6. Alessandro Borin & Riccardo Cristadoro & Roberto Golinelli & Giuseppe Parigi, 2012. "Forecasting world output: the rising importance of emerging economies," Temi di discussione (Economic working papers) 853, Bank of Italy, Economic Research and International Relations Area.
  7. Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in real-time: A density combination approach," Working Paper 2011/11, Norges Bank.
  8. Roman Horvath, 2012. "Do Confidence Indicators Help Predict Economic Activity? The Case of the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(5), pages 398-412, November.
  9. Anna Norin, 2011. "Nowcasting of the Gross Regional Product," ERSA conference papers ersa10p768, European Regional Science Association.

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