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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

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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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Publisher 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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  1. Stefan Gerlach & Matthew S. Yiu, 2004. "A Dynamic Factor Model for Current-Quarter Estimates of Economic Activity in Hong Kong," Working Papers 162004, Hong Kong Institute for Monetary Research. [Downloadable!]
  2. Hwee Kwan Chow & Keen Meng Choy, 2004. "Forecasting the Global Electronics Cycle with Leading Indicators: A VAR Approach," Working Papers 16-2004, Singapore Management University, School of Economics. [Downloadable!]
    Other versions:
  3. Fabio Canova & Matteo Ciccarelli, 2002. "Panel Index Var Models: Specification, Estimation, Testing And Leading Indicators," Working Papers. Serie AD 2002-21, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie). [Downloadable!]
    Other versions:
  4. Anindya BANERJEE & Massimiliano MARCELLINO, 2002. "Are There Any Reliable Leading Indicators for US Inflation and GDP Growth?," Economics Working Papers ECO2002/21, European University Institute. [Downloadable!]
    Other versions:
  5. Calista Cheung & Frédérick Demers, 2007. "Evaluating Forecasts from Factor Models for Canadian GDP Growth and Core Inflation," Working Papers 07-8, Bank of Canada. [Downloadable!]
  6. D R Osborn & M Sensier, 2002. "The Prediction of Business Cycle Phases: Financial Variables and International Linkages," Centre for Growth and Business Cycle Research Discussion Paper Series 15, Economics, The Univeristy of Manchester. [Downloadable!]
  7. Tak-Kuen Siu & Wai-Ki Ching & Eric Fung & Michael Ng, 2005. "Extracting Information from Spot Interest Rates and Credit Ratings using Double Higher-Order Hidden Markov Models," Computational Economics, Springer, vol. 26(3), pages 69-102, November. [Downloadable!] (restricted)
    Other versions:
  8. Elena Angelini & Gonzalo Camba-Mendez & Domenico Giannone & Lucrezia Reichlin & Gerhard Rünstler, 2008. "Short-Term Forecasts of Euro Area GDP Growth," ECARES Working Papers 2008_035, Université Libre de Bruxelles, Ecares. [Downloadable!]
    Other versions:
  9. Dreger, Christian & Schumacher, Christian, 2002. "Estimating Large-Scale Factor Models for Economic Activity in Germany: Do They Outperform Simpler Models?," Discussion Paper Series 26321, Hamburg Institute of International Economics. [Downloadable!]
  10. Declan Curran & Michael Funke, 2006. "Taking the Temperature - Forecasting GDP Growth for Mainland China," Quantitative Macroeconomics Working Papers 20606, Hamburg University, Department of Economics. [Downloadable!]
    Other versions:
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