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An automatic leading indicator of economic activity: forecasting GDP growth for European countries

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Author Info

  • GONZALO CAMBA-MENDEZ
  • GEORGE KAPETANIOS
  • RICHARD J. SMITH
  • MARTIN R. WEALE

Abstract

In the construction of a leading indicator model of economic activity, economists must select among a pool of variables which lead output growth. Usually the pool of variables is large and a selection of a subset must be carried out. This paper proposes an automatic leading indicator model which, rather than preselection, uses a dynamic factor model to summarize the information content of a pool of variables. Results using quarterly data for France, Germany, Italy and the United Kingdom show that the overall forecasting performance of the automatic leading indicator model appears better than that of more traditional VAR and BVAR models.

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Bibliographic Info

Article provided by Royal Economic Society in its journal The Econometrics Journal.

Volume (Year): 4 (2001)
Issue (Month): 1 ()
Pages: 37

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Handle: RePEc:ect:emjrnl:v:4:y:2001:i:1:p:37

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Related research

Keywords: Dynamic factor model; Forecasting; Kalman filter; AR; VAR and BVAR models.;

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Cited by:
  1. Katerina Arnostova & David Havrlant & Lubos Ruzicka & Peter Toth, 2010. "Short-Term Forecasting of Czech Quarterly GDP Using Monthly Indicators," Working Papers 2010/12, Czech National Bank, Research Department.

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