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Using factor models to construct composite indicators from BCS data - a comparison with European Commission confidence indicators

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  • Christian Gayer
  • Julien Genet

Abstract

This paper compares different approaches to constructing composite business cycle indicators based on series from the Joint Harmonised EU Programme of Business and Consumer Surveys (BCS). The currently computed Confidence Indicators are used as benchmarks in gauging four different factor-analytic methods to extract sectoral business cycle indicators. Improvements in tracking performance are mainly found on individual country level.

Suggested Citation

  • Christian Gayer & Julien Genet, 2006. "Using factor models to construct composite indicators from BCS data - a comparison with European Commission confidence indicators," European Economy - Economic Papers 2008 - 2015 240, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
  • Handle: RePEc:euf:ecopap:0240
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    References listed on IDEAS

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    Cited by:

    1. Andrea Carriero & Massimiliano Marcellino, 2011. "Sectoral Survey‐based Confidence Indicators for Europe," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(2), pages 175-206, April.
    2. Christian Dreger & Konstantin Arkadievich Kholodilin, 2013. "Forecasting Private Consumption by Consumer Surveys," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(1), pages 10-18, January.
    3. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2008. "A Monthly Indicator of the Euro Area GDP," Economics Working Papers ECO2008/32, European University Institute.
    4. Raffaele Mattera & Michelangelo Misuraca & Maria Spano & Germana Scepi, 2023. "Mixed frequency composite indicators for measuring public sentiment in the EU," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2357-2382, June.
    5. G. Bruno & L. Crosilla & P. Margani, 2019. "Inspecting the Relationship Between Business Confidence and Industrial Production: Evidence on Italian Survey Data," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(1), pages 1-24, April.
    6. Hyejung Moon & Jungick Lee, 2013. "Forecast evaluation of economic sentiment indicator for the Korean economy," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the Sixth IFC Conference on "Statistical issues and activities in a changing environment", Basel, 28-29 August 2012., volume 36, pages 180-190, Bank for International Settlements.
    7. Andreas Jonsson & Staffan Lindén, 2009. "The quest for the best consumer confidence indicator," European Economy - Economic Papers 2008 - 2015 372, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    8. Jonsson, Andreas & Lindén, Staffan, 2009. "The quest for the best consumer confidence indicator," MPRA Paper 25515, University Library of Munich, Germany.
    9. Piotr Białowolski, 2015. "Concepts of Confidence in Tendency Survey Research: An Assessment with Multi-group Confirmatory Factor Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 123(1), pages 281-302, August.

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