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Forecasting Inflation: An Art as Well as a Science!

  • Ard Reijer

    ()

  • Peter Vlaar

In this study we build two forecasting models to predict inflation for the Netherlands and for the euro area. Inflation is the yearly change of the Harmonised Index of Consumer Prices (HICP). The models provide point forecasts and prediction intervals for both the components of the HICP and the aggregated HICP-index itself. Both models are small-scale linear time series models allowing for long run equilibrium relationships between HICP components and other variables, notably the hourly wage rate and the import or producer prices. The model for the Netherlands is used to generate the Dutch inflation projections over a horizon of 11-15 months ahead for the eurosystem’s Narrow Inflation Projection Exercise (NIPE). The recursive forecast errors for several forecast horizons are evaluated for all models, and are found to outperform a naive forecast and optimal AR models. Moreover, the same result holds for the Dutch NIPE projections, which have been provided quarterly since 1999. The direct and aggregation methods to predict total HICP inflation perform about equally good

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Article provided by Springer in its journal De Economist.

Volume (Year): 154 (2006)
Issue (Month): 1 (03)
Pages: 19-40

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Handle: RePEc:kap:decono:v:154:y:2006:i:1:p:19-40
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  1. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
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  3. Garratt, Anthony & Kevin Lee & M Hashem Pesaran & Yongcheol Shin, 2002. "Forecast Uncertainties In Macroeconometric Modelling: An Application to the UK Economy," Royal Economic Society Annual Conference 2002 82, Royal Economic Society.
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  5. K. Hubrich, 2001. "Forecasting euro area inflation: Does contemponaneous aggregration improve the forecasting performance," WO Research Memoranda (discontinued) 661, Netherlands Central Bank, Research Department.
  6. Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2003. "Leading Indicators for Euro Area Inflation and GDP Growth," CEPR Discussion Papers 3893, C.E.P.R. Discussion Papers.
  7. 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.
  8. 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.
  9. Marcellino, Massimiliano, 1999. "Some Consequences of Temporal Aggregation in Empirical Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 129-36, January.
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  12. Hendry, D.F. & Mizon, G.E., 1999. "On selecting policy analysis models by forecast accuracy," Discussion Paper Series In Economics And Econometrics 9918, Economics Division, School of Social Sciences, University of Southampton.
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  14. Friedrich Fritzer & Gabriel Moser & Johann Scharler, 2002. "Forecasting Austrian HICP and its Components using VAR and ARIMA Models," Working Papers 73, Oesterreichische Nationalbank (Austrian Central Bank).
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  17. Benalal, Nicholai & Diaz del Hoyo, Juan Luis & Landau, Bettina & Roma, Moreno & Skudelny, Frauke, 2004. "To aggregate or not to aggregate? Euro area inflation forecasting," Working Paper Series 0374, European Central Bank.
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