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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;Working Papers Homepage.
  • Handle: RePEc:bde:wpaper:0419
    as

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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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    References listed on IDEAS

    as
    1. Annabelle Mourougane & Moreno Roma, 2003. "Can confidence indicators be useful to predict short term real GDP growth?," Applied Economics Letters, Taylor & Francis Journals, vol. 10(8), pages 519-522.
    2. Artis, Michael J & Zhang, Wenda, 1999. "Further Evidence on the International Business Cycle and the ERM: Is There a European Business Cycle?," Oxford Economic Papers, Oxford University Press, vol. 51(1), pages 120-132, January.
    3. Teresa Santero & Niels Westerlund, 1996. "Confidence Indicators and Their Relationship to Changes in Economic Activity," OECD Economics Department Working Papers 170, OECD Publishing.
    4. Mike Artis & Hans-Martin Krolzig & Juan Toro, 2004. "The European business cycle," Oxford Economic Papers, Oxford University Press, vol. 56(1), pages 1-44, January.
    5. Blake, Andrew P. & Camba-Mendez, Gonzalo, 1998. "Filtered least squares and measurement error," Economics Letters, Elsevier, vol. 59(2), pages 163-168, May.
    6. Michael ARTIS & Massimiliano MARCELLINO & Tommaso PROIETTI, 2002. "Dating the Euro Area Business Cycle," Economics Working Papers ECO2002/24, European University Institute.
    7. Hans-Martin Krolzig & Juan Toro, 2004. "Classical and modern business cycle measurement: The European case," Spanish Economic Review, Springer;Spanish Economic Association, vol. 7(1), pages 1-21, January.
    8. Victor Zarnowitz, 1992. "Business Cycles: Theory, History, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number zarn92-1, July.
    9. Hans-Martin Krolzig, 2001. "Markov-Switching Procedures for Dating the Euro-Zone Business Cycle," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 70(3), pages 339-351.
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    Citations

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    Cited by:

    1. 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.
    2. 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).
    3. 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.
    4. 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.
    5. Álvarez, L-J. & Bulligan, G. & Cabrero, A. & Ferrara, L. & Stahl, H., 2009. "Housing cycles in the major euro area countries," Working papers 269, Banque de France.
    6. Ferrara, Laurent, 2006. "A real-time recession indicator for the Euro area," MPRA Paper 4042, University Library of Munich, Germany.
    7. 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.
    8. 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.
    9. Javier Jareño, 2007. "Opinion-based surveys in the conjunctural analysis of the Spanish economy," Occasional Papers 0706, Banco de España;Occasional Papers Homepage.
    10. Adela Luque, 2005. "Skill mix and technology in Spain: evidence from firm level data," Working Papers 0513, Banco de España;Working Papers Homepage.
    11. 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..

    More about this item

    Keywords

    Business Cycle; Confidence Indicators; Markov Switching; Turning Points;

    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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