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

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

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.

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

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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/

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  1. Marcelle Chauvet & Zeynep Senyuz & Emre Yoldas, 2012. "What does financial volatility tell us about macroeconomic fluctuations?," Finance and Economics Discussion Series 2012-09, Board of Governors of the Federal Reserve System (U.S.).
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  3. Angelini, Elena & Camba-Mendez, Gonzalo & Giannone, Domenico & Reichlin, Lucrezia & Rünstler, Gerhard, 2008. "Short-term Forecasts of Euro Area GDP Growth," CEPR Discussion Papers 6746, C.E.P.R. Discussion Papers.
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  6. 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.
  7. 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.
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  10. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
  11. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
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  13. Helmut Lütkepohl, 2010. "Forecasting Aggregated Time Series Variables: A Survey," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,Centre for International Research on Economic Tendency Surveys, vol. 2010(2), pages 1-26.
  14. Domenico Giannone & Lucrezia Reichlin & David H Small, 2007. "Nowcasting GDP and Inflation: The Real-Time Informational Content of Macroeconomic Data Releases," Money Macro and Finance (MMF) Research Group Conference 2006 164, Money Macro and Finance Research Group.
  15. 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.
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  17. Laurent Ferrara & Clément Marsilli, 2012. "Financial variables as leading indicators of GDP growth: Evidence from a MIDAS approach during the Great Recession," EconomiX Working Papers 2012-19, University of Paris West - Nanterre la Défense, EconomiX.
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  25. repec:bla:buecrs:v:64:y:2012:i::p:s53-s70 is not listed on IDEAS
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  27. 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.
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