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Forecasting inflation: An art as well as a science!

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Author Info
Peter Vlaar
Ard den Reijer

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Abstract

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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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2004 with number 148.

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Date of creation: 11 Aug 2004
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Handle: RePEc:sce:scecf4:148

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Keywords: model selection; time series models; aggregation;

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Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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  3. Gabriel Moser & Fabio Rumler & Johann Scharler, 2004. "Forecasting Austrian Inflation," Working Papers 91, Oesterreichische Nationalbank (Austrian Central Bank). [Downloadable!]
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  4. Bruneau, C. & De Bandt, O. & Flageollet, A., 2003. "Forecasting Inflation in the Euro Area," Documents de Travail 102, Banque de France. [Downloadable!]
  5. 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. [Downloadable!] (restricted)
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  6. Anindya BANERJEE & Massimiliano MARCELLINO, 2002. "Are There Any Reliable Leading Indicators for US Inflation and GDP Growth?," Economics Working Papers ECO2002/21, European University Institute. [Downloadable!]
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  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. [Downloadable!]
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  10. Kirstin Hubrich, 2003. "Forecasting euro area inflation: does aggregating forecasts by HICP component improve forecast accuracy?," Working Paper Series 247, European Central Bank. [Downloadable!]
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  11. Canova, Fabio, 2002. "G-7 Inflation Forecasts," CEPR Discussion Papers 3283, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  13. Peter F. Christoffersen & Francis X. Diebold, 1997. "Cointegration and Long-Horizon Forecasting," NBER Technical Working Papers 0217, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  14. K. Hubrich, 2001. "Forecasting euro area inflation: Does contemponaneous aggregration improve the forecasting performance," WO Research Memoranda (discontinued) 661, Netherlands Central Bank, Research Department. [Downloadable!]
  15. 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. [Downloadable!] (restricted)
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  16. 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.
  17. Garrat, A. & Lee, K. & Pesaran, M.H. & Shin, Y., 2000. "Forecast Uncertainties in Macroeconometric Modelling: An Application to the UK Economy," Cambridge Working Papers in Economics 0004, Faculty of Economics, University of Cambridge. [Downloadable!]
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  18. Inoue, Atsushi & Kilian, Lutz, 2006. "On the selection of forecasting models," Journal of Econometrics, Elsevier, vol. 130(2), pages 273-306, February. [Downloadable!] (restricted)
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  19. 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). [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Rebeca Albacete & Antoni Espasa, 2005. "Forecasting Inflation In The Euro Area Using Monthly Time Series Models And Quarterly Econometric Models," Statistics and Econometrics Working Papers ws050401, Universidad Carlos III, Departamento de Estadística y Econometría. [Downloadable!]
  2. Demertzis, Maria & Hughes Hallett, Andrew, 2005. "Forming Rational Expectations and When it is Right to be 'Wrong'," CEPR Discussion Papers 5042, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
  3. Janine Aron & John Muellbauer, 2008. "New methods for forecasting inflation and its sub-components: application to the USA," Economics Series Working Papers 406, University of Oxford, Department of Economics. [Downloadable!]
  4. Nicholai Benalal & Juan Luis Diaz del Hoyo & Bettina Landau & Moreno Roma & Frauke Skudelny, 2004. "To aggregate or not to aggregate? Euro area inflation forecasting," Working Paper Series 374, European Central Bank. [Downloadable!]
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