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Forecasting inflation: An art as well as a science!

  • P.J.G. Vlaar
  • A.H.J. den Reijer

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 an 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. 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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File URL: http://www.dnb.nl/binaries/staff107_tcm46-146884.pdf
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Paper provided by Netherlands Central Bank in its series DNB Staff Reports (discontinued) with number 107.

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Length: 37 pages
Date of creation: 2003
Date of revision:
Handle: RePEc:dnb:staffs:107
Contact details of provider: Postal: Postbus 98, 1000 AB Amsterdam
Web page: http://www.dnb.nl/en/

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  1. repec:sae:niesru:v:167:y::i:1:p:106-112 is not listed on IDEAS
  2. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
  3. Kirstin Hubrich, 2004. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," Computing in Economics and Finance 2004 230, Society for Computational Economics.
  4. K. Hubrich, 2001. "Forecasting euro area inflation: Does contemponaneous aggregration improve the forecasting performance," WO Research Memoranda (discontinued) 661, Netherlands Central Bank, Research Department.
  5. Peter F. Christoffersen & Francis X. Diebold, 1997. "Cointegration and long-horizon forecasting," Working Papers 97-14, Federal Reserve Bank of Philadelphia.
  6. M. Hashem Pesaran, 2000. "Forecast Uncertainties in Macroeconometric Modelling: An Application to the UK Economy," CESifo Working Paper Series 345, CESifo Group Munich.
  7. 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.
  8. Gabriel Moser & Fabio Rumler & Johann Scharler, 2004. "Forecasting Austrian Inflation," Working Papers 91, Oesterreichische Nationalbank (Austrian Central Bank).
  9. Hendry, David F & Michael P. Clements, 2002. "Economic Forecasting: Some Lessons from Recent Research," Royal Economic Society Annual Conference 2002 99, Royal Economic Society.
  10. Banerjee, Anindya & Marcellino, Massimiliano, 2006. "Are there any reliable leading indicators for US inflation and GDP growth?," International Journal of Forecasting, Elsevier, vol. 22(1), pages 137-151.
  11. 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.
  12. James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc.
  13. Inoue, Atsushi & Kilian, Lutz, 2006. "On the selection of forecasting models," Journal of Econometrics, Elsevier, vol. 130(2), pages 273-306, February.
  14. Lutz Kilian, 1998. "Small-Sample Confidence Intervals For Impulse Response Functions," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 218-230, May.
  15. 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).
  16. Canova, Fabio, 2002. "G-7 Inflation Forecasts," CEPR Discussion Papers 3283, C.E.P.R. Discussion Papers.
  17. 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.
  18. 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.
  19. 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.
  20. Bruneau, C. & De Bandt, O. & Flageollet, A., 2003. "Forecasting Inflation in the Euro Area," Working papers 102, Banque de France.
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