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Sectoral Survey-based Confidence Indicators for Europe

  • Andrea Carriero
  • Massimiliano Marcellino

In this paper we analyze a novel dataset of Business and Consumer Surveys, using dynamic factor techniques, to produce composite coincident indices (CCIs) at the sectoral level for the European countries and for Europe as a whole. Few CCIs are available for Europe compared to the US, and most of them use macroeconomic variables and focus on aggregate activity. However, there are often delays in the release of macroeconomic data, later revisions, and differences in the definition of the variables across countries, while the surveys are timely available, not subject to revision, and fully comparable across countries. Moreover, there are substantial discrepancies in activity at the sectoral level, which justifies the interest in a sectoral disaggregation. Compared to the Confidence Indicators produced by the European Commission, which are based on a simple average of the aggregate survey answers, we show that factor based CCIs, using survey answers at a more disaggregate level, produce higher correlation with the reference series for the majority of sectors and countries.

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Paper provided by IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University in its series Working Papers with number 320.

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Date of creation: 2007
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Handle: RePEc:igi:igierp:320
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  1. 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 240, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
  2. Forni, Mario, et al, 2001. "Coincident and Leading Indicators for the Euro Area," Economic Journal, Royal Economic Society, vol. 111(471), pages C62-85, May.
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  11. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
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  15. Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
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