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Forecasting Inflation in the Euro Area

Author

Listed:
  • Bruneau, C.
  • De Bandt, O.
  • Flageollet, A.

Abstract

In order to provide medium run forecasts of headline and core HICP inflation for the euro area, we assess the usefulness of dynamic factor models. We use Stock and Watson's (1999) out-of-sample methodology for models estimated over the 1988:1-2002:3 period, with balanced and unbalanced panels. We provide evidence that factors alone or combined with indicators help improve upon the simple Autoregressive (AR) model for forecasting HICP core inflation as well total inflation, if one refers to the usual criterion of "Relative MSE" together with its standard deviation. However, regarding total HICP we do not produce forecasts that are totally satisfactory in the sense of being capable of recognizing the 1999-2000 upturn in inflation in a timely manner. But, from that point of view, the construction of a ''synthetic core'' indicator helps achieve significantly better forecasts over a 12-month horizon than the AR model for total inflation for the final part of the sample. We also show that the results are rather robust to potential data-snooping.

Suggested Citation

  • Bruneau, C. & De Bandt, O. & Flageollet, A., 2003. "Forecasting Inflation in the Euro Area," Working papers 102, Banque de France.
    • Handle: RePEc:bfr:banfra:102
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    References listed on IDEAS

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    Cited by:

    1. Christian Bordes & Laurent Clerc, 2007. "Price Stability And The Ecb'S Monetary Policy Strategy," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 268-326, April.
    2. Bruneau, C. & De bandt, O. & Flageollet, A., 2004. "Inflation and the Markup in the Euro Area," Working papers 114, Banque de France.
    3. Ard Reijer & Peter Vlaar, 2006. "Forecasting Inflation: An Art as Well as a Science!," De Economist, Springer, vol. 154(1), pages 19-40, March.
    4. Sandra Eickmeier & Christina Ziegler, 2008. "How successful are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 237-265.
    5. Calista Cheung & Frédérick Demers, 2007. "Evaluating Forecasts from Factor Models for Canadian GDP Growth and Core Inflation," Staff Working Papers 07-8, Bank of Canada.
    6. Tumala, Mohammed M & Olubusoye, Olusanya E & Yaaba, Baba N & Yaya, OlaOluwa S & Akanbi, Olawale B, 2017. "Forecasting Nigerian Inflation using Model Averaging methods: Modelling Frameworks to Central Banks," MPRA Paper 88754, University Library of Munich, Germany, revised Feb 2018.

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    More about this item

    Keywords

    Inflation ; Out-of-sample forecast ; Indicator models ; Dynamic factor models ; Phillips curve ; Euro area ; Data snooping;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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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