IDEAS home Printed from https://ideas.repec.org/a/bfr/quarte/20112407.html
   My bibliography  Save this article

Forecasting the business cycle. Summary of the 8th International Institute of Forecasters workshop hosted by the Banque de France on 1-2 December 2011 in Paris

Author

Listed:
  • L. Ferrara.

Abstract

In the wake of the recent international economic recession in 2008-2009, forecasting methods designed to anticipate business cycles have been widely revisited. Recent innovative econometric methods were presented and widely discussed by academics and economists from international and national institutions at the latest IIF workshop which was hosted by the Banque de France in Paris on 1-2 December 2011.

Suggested Citation

  • L. Ferrara., 2011. "Forecasting the business cycle. Summary of the 8th International Institute of Forecasters workshop hosted by the Banque de France on 1-2 December 2011 in Paris," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 24, pages 135-144, Winter.
    • Handle: RePEc:bfr:quarte:2011:24:07
    as

    Download full text from publisher

    File URL: https://publications.banque-france.fr/sites/default/files/medias/documents/quarterly-selection-of-articles_24_2011-2012-winter.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
    2. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
    3. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, May.
    4. Hamilton, James D., 2011. "Calling recessions in real time," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1006-1026, October.
    5. Laurent Ferrara, 2009. "Caractérisation et datation des cycles économiques en zone euro," Revue économique, Presses de Sciences-Po, vol. 60(3), pages 703-712.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
    2. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
    3. Sergey V. Smirnov & Nikolay V. Kondrashov & Anna V. Petronevich, 2017. "Dating Cyclical Turning Points for Russia: Formal Methods and Informal Choices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 13(1), pages 53-73, May.
    4. Alejandro López-Vera & Andrés D. Pinchao-Rosero & Norberto Rodríguez-Niño, 2018. "Non-Linear Fiscal Multipliers for Public Expenditure and Tax Revenue in Colombia," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 36(85), pages 48-64, April.
    5. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    6. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    7. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018. "Combined Density Nowcasting in an Uncertain Economic Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 131-145, January.
    8. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    9. Dalibor Stevanovic, 2013. "Probability and Severity of Recessions," CIRANO Working Papers 2013s-43, CIRANO.
    10. Steffen R. Henzel & Malte Rengel, 2017. "Dimensions Of Macroeconomic Uncertainty: A Common Factor Analysis," Economic Inquiry, Western Economic Association International, vol. 55(2), pages 843-877, April.
    11. Kim, Kun Ho, 2011. "Density forecasting through disaggregation," International Journal of Forecasting, Elsevier, vol. 27(2), pages 394-412.
    12. Martínez-Martín, Jaime & Rusticelli, Elena, 2021. "Keeping track of global trade in real time," International Journal of Forecasting, Elsevier, vol. 37(1), pages 224-236.
    13. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    14. 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.
    15. Agnello, Luca & Schuknecht, Ludger, 2011. "Booms and busts in housing markets: Determinants and implications," Journal of Housing Economics, Elsevier, vol. 20(3), pages 171-190, September.
    16. Camacho, Maximo & Perez-Quiros, Gabriel & Poncela, Pilar, 2018. "Markov-switching dynamic factor models in real time," International Journal of Forecasting, Elsevier, vol. 34(4), pages 598-611.
    17. Antonello D’Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2016. "Nowcasting Business Cycles: A Bayesian Approach to Dynamic Heterogeneous Factor Models," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 569-594, Emerald Group Publishing Limited.
    18. Serati, Massimiliano & Manera, Matteo & Plotegher, Michele, 2008. "Modeling Electricity Prices: From the State of the Art to a Draft of a New Proposal," International Energy Markets Working Papers 44426, Fondazione Eni Enrico Mattei (FEEM).
    19. Duprey, Thibaut & Klaus, Benjamin & Peltonen, Tuomas, 2017. "Dating systemic financial stress episodes in the EU countries," Journal of Financial Stability, Elsevier, vol. 32(C), pages 30-56.
    20. Maximo Camacho & Gabriel Perez‐Quiros & Pilar Poncela, 2015. "Extracting Nonlinear Signals from Several Economic Indicators," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1073-1089, November.

    More about this item

    Keywords

    business cycles; forecasting; recession; econometric modelling; density forecasts; leading indicators.;
    All these keywords.

    JEL classification:

    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • 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
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bfr:quarte:2011:24:07. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michael brassart (email available below). General contact details of provider: https://edirc.repec.org/data/bdfgvfr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.