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Forecasting inflation in France

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  • Célérier, C.

Abstract

The paper develops a model for forecasting inflation in France. As this model has to be integrated in the Eurosystem projection exercises, the projections are conditional to specific assumptions and must be consistent with the Macroeconomic projection exercise of the Banque de France. The specification of the model is thus highly constrained. The theoretical foundations of the model are based on the markup model for prices, but the resulting empirical model also has elements relating to the purchasing power parity and the Phillips curve. The model aggregates forecasts of the main HICP subcomponents. We show that the model exhibits better performance than a standard AR(4) model.

Suggested Citation

  • Célérier, C., 2009. "Forecasting inflation in France," Working papers 262, Banque de France.
    • Handle: RePEc:bfr:banfra:262
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    References listed on IDEAS

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    1. Pierre Biscourp & Xavier Boutin & Thibaud Vergé, 2013. "The Effects of Retail Regulations on Prices: Evidence from the Loi Galland," Economic Journal, Royal Economic Society, vol. 123(12), pages 1279-1312, December.
    2. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    3. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
    4. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
    5. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    6. Erik Britton & Jens D J Larsen & Ian Small, 2000. "Imperfect competition and the dynamics of mark-ups," Bank of England working papers 110, Bank of England.
    7. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    8. Marianne Bertrand & Francis Kramarz, 2002. "Does Entry Regulation Hinder Job Creation? Evidence from the French Retail Industry," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1369-1413.
    9. James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
    10. Hubrich, Kirstin, 2005. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," International Journal of Forecasting, Elsevier, vol. 21(1), pages 119-136.
    11. Duarte, Claudia & Rua, Antonio, 2007. "Forecasting inflation through a bottom-up approach: How bottom is bottom?," Economic Modelling, Elsevier, vol. 24(6), pages 941-953, November.
    12. Philippe Askenazy & Katia Weidenfeld, 2007. "Les soldes de la loi Raffarin," PSE-Ecole d'économie de Paris (Postprint) halshs-00754858, HAL.
    13. Allain Marie-Laure & Chambolle Claire, 2005. "Loss-Leaders Banning Laws as Vertical Restraints," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 3(1), pages 1-25, February.
    14. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    15. O. De Bandt & E. Michaux & C. Bruneau & A. Flageollet, 2007. "Forecasting inflation using economic indicators: the case of France," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 1-22.
    16. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501, Decembrie.
    17. Neil R. Ericsson & James G. MacKinnon, 2002. "Distributions of error correction tests for cointegration," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 285-318, June.
    18. J. C. G. Boot & W. Feibes & J. H. C. Lisman, 1967. "Further Methods of Derivation of Quarterly Figures from Annual Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 16(1), pages 65-75, March.
    19. Fernandez, Roque B, 1981. "A Methodological Note on the Estimation of Time Series," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 471-476, August.
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    Cited by:

    1. Boris I. Alekhin, 2023. "Interregional Differences in Inflation through the Prism of Ackley’s Theory," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 1, pages 8-25, February.
    2. Ivan Kitov & Oleg Kitov, 2013. "Does Banque de France control inflation and unemployment?," Papers 1311.1097, arXiv.org.

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    More about this item

    Keywords

    Inflation ; Out-of-sample forecast ; Economic modelling.;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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