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A useful tool to identify recessions in the euro-area

Author

Listed:
  • Pilar Bengoechea

    (European Commission)

  • Gabriel Pérez-Quirós

    (Banco de España)

Abstract

This paper investigates the identification and dating of the European business cycle, using different methods. We concentrate on methods and statistical series that provides timely and accurate information about the contemporaneous state of the economy in order to provide the reader with a useful tool that allows him or her to analyze current business conditions and make predictions about the future state of the economy. In this spirit, we find that the European Commission industrial confidence indicator (ICI) is useful in providing that information.

Suggested Citation

  • Pilar Bengoechea & Gabriel Pérez-Quirós, 2004. "A useful tool to identify recessions in the euro-area," Working Papers 0419, Banco de España.
  • Handle: RePEc:bde:wpaper:0419
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    File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/04/Fic/dt0419e.pdf
    File Function: First version, November 2004
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    Citations

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    Cited by:

    1. Olivier Darné & Laurent Ferrara, 2011. "Identification of Slowdowns and Accelerations for the Euro Area Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(3), pages 335-364, June.
    2. Charles, Amélie & Darné, Olivier & Diebolt, Claude & Ferrara, Laurent, 2015. "A new monthly chronology of the US industrial cycles in the prewar economy," Journal of Financial Stability, Elsevier, vol. 17(C), pages 3-9.
    3. lvarez, L-J. & Bulligan, G. & Cabrero, A. & Laurent Ferrara & Stahl, H., 2009. "Housing cycles in the major euro area countries," Working papers 269, Banque de France.
    4. Ferrara, Laurent, 2006. "A real-time recession indicator for the Euro area," MPRA Paper 4042, University Library of Munich, Germany.
    5. Gagea Mariana, 2012. "Study of Industrial Conjuncture Balances in Romania, Using Logit Model with Heteroscedasticity," Scientific Annals of Economics and Business, Sciendo, vol. 59(1), pages 337-349, July.
    6. Ramón Cobo-Reyes & Gabriel Pérez Quirós, 2005. "The effect of oil price on industrial production and on stock returns," ThE Papers 05/18, Department of Economic Theory and Economic History of the University of Granada..
    7. Charlotte Le Chapelain, 2012. "Allocation des talents et accumulation de capital humain en France à la fin du XIXe siècle," Working Papers 12-03, Association Française de Cliométrie (AFC).
    8. Peter Martey Addo & Monica Billio & Dominique Guegan, 2013. "Turning point chronology for the Euro-Zone: A Distance Plot Approach," Documents de travail du Centre d'Economie de la Sorbonne 13025, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    9. Sylvia Kaufmann, 2010. "Dating and forecasting turning points by Bayesian clustering with dynamic structure: a suggestion with an application to Austrian data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 309-344.
    10. Olivier Biau & Hélène Erkel-Rousse & Nicolas Ferrari, 2006. "Réponses individuelles aux enquêtes de conjoncture et prévision de la production manufacturière," Économie et Statistique, Programme National Persée, vol. 395(1), pages 91-116.
    11. Javier Jareño, 2007. "Opinion-based surveys in the conjunctural analysis of the Spanish economy," Occasional Papers 0706, Banco de España.
    12. Nissilä, Wilma, 2020. "Probit based time series models in recession forecasting – A survey with an empirical illustration for Finland," BoF Economics Review 7/2020, Bank of Finland.
    13. Adela Luque, 2005. "Skill mix and technology in Spain: evidence from firm level data," Working Papers 0513, Banco de España.
    14. repec:onb:oenbwp:y::i:144:b:1 is not listed on IDEAS
    15. Jacques Anas & Monica Billio & Laurent Ferrara & Gian Luigi Mazzi, 2008. "A System For Dating And Detecting Turning Points In The Euro Area," Manchester School, University of Manchester, vol. 76(5), pages 549-577, September.

    More about this item

    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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