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Monthly forecasting of French GDP: A revised version of the OPTIM model

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Author Info

  • Barhoumi, K.
  • Brunhes-Lesage, V.
  • Darné, O.
  • Ferrara, L.
  • Pluyaud, B.
  • Rouvreau, B.

Abstract

This paper presents a revised version of the model OPTIM, proposed by Irac and Sédillot (2002), used at the Banque de France in order to predict French GDP quarterly growth rate, for the current and next quarters. The model is designed to be used on a monthly basis by integrating monthly economic information through bridge models, for both supply and demand sides of GDP. For each GDP component, bridge equations are specified by using a general-to-specific approach implemented in an automated way by Hoover and Perez (1999) and improved by Krolzig and Hendry (2001). This approach allows to select explanatory variables among a large data set of hard and soft data. The final choice of equations relies on a recursive forecast study, which also helps to assess the forecasting performance of the revised OPTIM model in the prediction of aggregated GDP. This study is based on pseudo real-time forecasts taking publication lags into account. It turns out that the model outperforms benchmark models.

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Bibliographic Info

Paper provided by Banque de France in its series Working papers with number 222.

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Length: 44 pages
Date of creation: 2008
Date of revision:
Handle: RePEc:bfr:banfra:222

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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Related research

Keywords: GDP forecasting ; Bridge models ; General-to-specific approach;

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References

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  1. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2005. "Leading Indicators for Euro-area Inflation and GDP Growth," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 785-813, December.
  2. Bańbura, Marta & Rünstler, Gerhard, 2011. "A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP," International Journal of Forecasting, Elsevier, vol. 27(2), pages 333-346.
  3. Hans-Martin Krolzig & David Hendry, 1999. "Computer Automation of General-to-Specific Model Selection Procedures," Computing in Economics and Finance 1999 314, Society for Computational Economics.
  4. 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.
  5. 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.
  6. Kevin D. Hoover & Stephen J. Perez, . "Data Mining Reconsidered: Encompassing And The General-To-Specific Approach To Specification Search," Department of Economics 97-27, California Davis - Department of Economics.
  7. 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.
  8. Franck Sédillot & Nigel Pain, 2003. "Indicator Models of Real GDP Growth in Selected OECD Countries," OECD Economics Department Working Papers 364, OECD Publishing.
  9. Irac, D. & Sédillot, F., 2002. "Short-Run Assessment of French Economic Activity Using OPTIM," Working papers 88, Banque de France.
  10. Hansson, Jesper & Jansson, Per & Lof, Marten, 2005. "Business survey data: Do they help in forecasting GDP growth?," International Journal of Forecasting, Elsevier, vol. 21(2), pages 377-389.
  11. David Hendry & Hans-Martin Krolzig, 2003. "Sub-Sample Model Selection Procedures in Gets Modelling," Economics Series Working Papers 2003-W17, University of Oxford, Department of Economics.
  12. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2002. "Do Financial Variables Help Forecasting Inflation and Real Activity in the Euro Area?," CEPR Discussion Papers 3146, C.E.P.R. Discussion Papers.
  13. Robert Ingenito & Bharat Trehan, 1996. "Using monthly data to predict quarterly output," Economic Review, Federal Reserve Bank of San Francisco, pages 3-11.
  14. 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.
  15. Coutino, Alfredo, 2005. "On the use of high-frequency economic information to anticipate the current quarter GDP: A study case for Mexico," Journal of Policy Modeling, Elsevier, vol. 27(3), pages 327-344, April.
  16. Schumacher, Christian & Breitung, Jörg, 2006. "Real-time forecasting of GDP based on a large factor model with monthly and quarterly data," Discussion Paper Series 1: Economic Studies 2006,33, Deutsche Bundesbank, Research Centre.
  17. 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.
  18. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, Elsevier.
  19. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  20. Jennifer L. Castle, 2005. "Evaluating PcGets and RETINA as Automatic Model Selection Algorithms," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 837-880, December.
  21. Perez-Amaral, Teodosio & Gallo, Giampiero M. & White, Halbert, 2005. "A COMPARISON OF COMPLEMENTARY AUTOMATIC MODELING METHODS: RETINA AND PcGets," Econometric Theory, Cambridge University Press, vol. 21(01), pages 262-277, February.
  22. Baffigi, Alberto & Golinelli, Roberto & Parigi, Giuseppe, 2004. "Bridge models to forecast the euro area GDP," International Journal of Forecasting, Elsevier, vol. 20(3), pages 447-460.
  23. Golinelli, Roberto & Parigi, Giuseppe, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
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Citations

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Cited by:
  1. Guido Bulligan & Massimiliano Marcellino & Fabrizio Venditti, 2012. "Forecasting economic activity with higher frequency targeted predictors," Temi di discussione (Economic working papers) 847, Bank of Italy, Economic Research and International Relations Area.
  2. Katja Drechsel & R. Scheufele, 2013. "Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment," IWH Discussion Papers 7, Halle Institute for Economic Research.
  3. Robert Lehmann & Klaus Wohlrabe, 2014. "Forecasting gross value-added at the regional level: are sectoral disaggregated predictions superior to direct ones?," Jahrbuch für Regionalwissenschaft, Springer, vol. 34(1), pages 61-90, February.
  4. Tomasz Jasiński & Paweł Mielcarz, 2013. "Consumption as a Factor of Polish Economic Growth During the Global Recession of 2008/2009: A Comparison with Spain and Hungary," Contemporary Economics, University of Finance and Management in Warsaw, vol. 7(2), June.
  5. Paulo Soares Esteves & António Rua, 2012. "Short-term forecasting for the portuguese economy: a methodological overview," Economic Bulletin and Financial Stability Report Articles, Banco de Portugal, Economics and Research Department.
  6. Bessec, M., 2012. "Short-term forecasts of French GDP: a dynamic factor model with targeted predictors," Working papers 409, Banque de France.
  7. Ferrara, L., 2008. "The contribution of cyclical turning point indicators to business cycle analysis," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 13, pages 49-61, Autumn.
  8. Lehmann, Robert & Wohlrabe, Klaus, 2013. "Sectoral gross value-added forecasts at the regional level: Is there any information gain?," MPRA Paper 46765, University Library of Munich, Germany.
  9. Barhoumi, K. & Brunhes-Lesage, V. & Ferrara, L. & Pluyaud, B. & Rouvreau, B. & Darné, O., 2008. "OPTIM: a quarterly forecasting tool for French GDP," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 13, pages 31-47, Autumn.

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