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Forecast Evaluation of European Commission Survey Indicators

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  • Christian Gayer

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    Abstract

    This study examines the contribution of several survey indicators published by the European Commission to forecasting overall economic activity in the euro area. It entails a quantitative evaluation of the information content of seven composite indicators with regard to GDP growth. A preliminary analysis looks at the stationarity and correlation properties of the variables. Based on bivariate VAR-models and the notion of forecast improvement, the methodological approach is two-fold: In a first step, the focussed relations are studied from an ex post perspective. Employing standard and individual Granger-causality tests, an initial assessment of the mean predictive content of the indicators is provided.

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    File URL: http://dx.doi.org/10.1787/jbcma-v2005-art2-en
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    Bibliographic Info

    Article provided by OECD Publishing,CIRET in its journal Journal of Business Cycle Measurement and Analysis.

    Volume (Year): 2005 (2005)
    Issue (Month): 2 ()
    Pages: 157-183

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    Handle: RePEc:oec:stdkaa:5l9vc43c09ms

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    Related research

    Keywords: Business Cycle; Confidence Indicators; Forecasting; Forecast Evaluation;

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    Cited by:
    1. Christian Seiler, 2013. "Nonresponse in Business Tendency Surveys: Theoretical Discourse and Empirical Evidence," ifo Beiträge zur Wirtschaftsforschung, Ifo Institute for Economic Research at the University of Munich, number 52.
    2. 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.
    3. Michael Graff, 2006. "Ein multisektoraler Sammelindikator für die Schweizer Konjunktur," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 142(IV), pages 529–577, December.
    4. Christian Seiler, 2012. "On the Robustness of the Balance Statistics with respect to Nonresponse," Ifo Working Paper Series Ifo Working Paper No. 126, Ifo Institute for Economic Research at the University of Munich.

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