Advanced Search
MyIDEAS: Login to save this paper or follow this series

Forecasting growth during the Great Recession: is financial volatility the missing ingredient?

Contents:

Author Info

  • Ferrara, L.
  • Marsilli, C.
  • Ortega, J-P.

Abstract

The Great Recession endured by the main industrialized countries during the period 2008–2009, in the wake of the financial and banking crisis, has pointed out the major role of the financial sector on macroeconomic fluctuations. In this respect, many researchers have started to reconsider the linkages between financial and macroeconomic areas. In this paper, we evaluate the leading role of the daily volatility of two major financial variables, namely commodity and stock prices, in their ability to anticipate the output growth. For this purpose, we propose an extended MIDAS (Mixed Data Sampling) model that allows the forecasting of the quarterly output growth rate using exogenous variables sampled at various higher frequencies. Empirical results on three industrialized countries (US, France, and UK) show that mixing daily financial volatilities and monthly industrial production is useful at the time of predicting gross domestic product growth over the Great Recession period.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.banque-france.fr/uploads/tx_bdfdocumentstravail/DT-454_01.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Banque de France in its series Working papers with number 454.

as in new window
Length: 22 pages
Date of creation: 2013
Date of revision:
Handle: RePEc:bfr:banfra:454

Contact details of provider:
Postal: Banque de France 31 Rue Croix des Petits Champs LABOLOG - 49-1404 75049 PARIS
Web page: http://www.banque-france.fr/
More information through EDIRC

Related research

Keywords: Great Recession; GDP Forecasting; Financial variables; MIDAS approach; Volatility.;

Other versions of this item:

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. O. E. Barndorff-Nielsen & P. Reinhard Hansen & A. Lunde & N. Shephard, 2009. "Realized kernels in practice: trades and quotes," Econometrics Journal, Royal Economic Society, vol. 12(3), pages C1-C32, November.
  2. Anna Creti & Marc Joëts & Valérie Mignon, 2012. "On the links between stock and commodity markets' volatility," EconomiX Working Papers 2012-42, University of Paris West - Nanterre la Défense, EconomiX.
  3. Guillaume Chevillon, 2005. "Direct multi-step estimation and forecasting," Documents de Travail de l'OFCE 2005-10, Observatoire Francais des Conjonctures Economiques (OFCE).
  4. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, Elsevier.
  5. Diron, Marie, 2006. "Short-term forecasts of euro area real GDP growth: an assessment of real-time performance based on vintage data," Working Paper Series 0622, European Central Bank.
  6. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
  7. Charles, Amelie & Darne, Olivier, 2005. "Outliers and GARCH models in financial data," Economics Letters, Elsevier, vol. 86(3), pages 347-352, March.
  8. Carnero, M. Angeles & Peña, Daniel & Ruiz, Esther, 2012. "Estimating GARCH volatility in the presence of outliers," Economics Letters, Elsevier, vol. 114(1), pages 86-90.
  9. Simpson, Paul W & Osborn, Denise R & Sensier, Marianne, 2001. "Forecasting UK Industrial Production over the Business Cycle," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(6), pages 405-24, September.
  10. Angelini, Elena & Camba-Méndez, Gonzalo & Giannone, Domenico & Rünstler, Gerhard & Reichlin, Lucrezia, 2008. "Short-term forecasts of euro area GDP growth," Working Paper Series 0949, European Central Bank.
  11. Lutz Kilian, 2008. "The Economic Effects of Energy Price Shocks," Journal of Economic Literature, American Economic Association, vol. 46(4), pages 871-909, December.
  12. Claessens, Stijn & Kose, Ayhan & Terrones, Marco E, 2011. "How Do Business and Financial Cycles Interact?," CEPR Discussion Papers 8396, C.E.P.R. Discussion Papers.
  13. Chauvet, Marcelle & Senyuz, Zeynep & Yoldas, Emre, 2010. "What does financial volatility tell us about macroeconomic fluctuations?," MPRA Paper 34104, University Library of Munich, Germany, revised Jun 2011.
  14. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," University of California at Los Angeles, Anderson Graduate School of Management qt9mf223rs, Anderson Graduate School of Management, UCLA.
  15. repec:bla:buecrs:v:64:y:2012:i::p:s53-s70 is not listed on IDEAS
  16. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
  17. Hamilton, James D., 2003. "What is an oil shock?," Journal of Econometrics, Elsevier, vol. 113(2), pages 363-398, April.
  18. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
  19. James H. Stock & Mark W. Watson, 2001. "Forecasting output and inflation: the role of asset prices," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  20. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
  21. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2013. "Should Macroeconomic Forecasters Use Daily Financial Data and How?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 240-251, April.
  22. Laurent Ferrara & Clément Marsilli, 2013. "Financial variables as leading indicators of GDP growth: Evidence from a MIDAS approach during the Great Recession," Applied Economics Letters, Taylor & Francis Journals, vol. 20(3), pages 233-237, February.
  23. Massimiliano Marcellino & Christian Schumacher, 2010. "Factor MIDAS for Nowcasting and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(4), pages 518-550, 08.
  24. Clements, Michael P & Galvão, Ana Beatriz, 2008. "Macroeconomic Forecasting With Mixed-Frequency Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 546-554.
  25. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  26. Helmut Luetkepohl, 2009. "Forecasting Aggregated Time Series Variables: A Survey," Economics Working Papers ECO2009/17, European University Institute.
  27. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  28. Bellégo, C. & Ferrara, L., 2012. "Macro-financial linkages and business cycles: A factor-augmented probit approach," Economic Modelling, Elsevier, vol. 29(5), pages 1793-1797.
  29. Eun Ahn & Jin Man Lee, 2006. "Volatility relationship between stock performance and real output," Applied Financial Economics, Taylor & Francis Journals, vol. 16(11), pages 777-784.
  30. Hamilton, James D & Gang, Lin, 1996. "Stock Market Volatility and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 573-93, Sept.-Oct.
Full references (including those not matched with items on IDEAS)

Citations

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:bfr:banfra:454. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael brassart).

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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