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Forecasting Austrian HICP and its Components using VAR and ARIMA Models

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Author Info
Friedrich Fritzer () (Oesterreichische Nationalbank, Economic Analysis Division, Otto-Wagner Platz 3, POB 61, A-1011 Vienna)
Gabriel Moser () (Oesterreichische Nationalbank, Otto-Wagner Platz 3, POB 61, A-1011 Vienna)
Johann Scharler () (Simon Fraser University, Department of Economics, 8888 University Drive, Burnaby, B.C., Canada V5A 1S6)

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Abstract

The purpose of this paper is to evaluate the performance of VAR and ARIMA models to forecast Austrian HICP inflation. Additionally, we investigate whether disaggregate modelling of five subcomponents of inflation is superior to specifications of headline HICP inflation. Our modelling procedure is to find adequate VAR and ARIMA specifications that minimise the 12 months out-of-sample forecasting error. The main findings are twofold. First, VAR models outperform the ARIMA models in terms of forecasting accuracy over the longer pro- jection horizon (8 to 12 months ahead). Second, a disaggregated ap- proach improves forecasting accuracy substantially for ARIMA mod- els. In case of the VAR approach the superiority of modelling the five subcomponents instead of just considering headline HICP inflation is demonstrated only over the longer period (10 to 12 months ahead).

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Publisher Info
Paper provided by Oesterreichische Nationalbank (Austrian Central Bank) in its series Working Papers with number 73.

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Length: 49 pages
Date of creation: 26 Aug 2002
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Handle: RePEc:onb:oenbwp:73

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Postal: P.O. Box 61, A-1011 Vienna, Austria
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Postal: Oesterreichische Nationalbank, Economic Studies Division, c/o Beate Hofbauer-Berlakovich, POB 61, A-1011 Vienna, Austria
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Related research
Keywords: VAR and ARIMA models in ation forecasting automatic modelling forecasting accuracy.

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Find related papers by JEL classification:
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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References listed on IDEAS
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. David F. Hendry & Michael P. Clements, 2001. "Economic forecasting: some lessons from recent research," Working Paper Series 082, European Central Bank. [Downloadable!]
    Other versions:
  2. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January. [Downloadable!] (restricted)
  3. 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.
  4. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October. [Downloadable!] (restricted)
    Other versions:
  5. Clements, M.P. & Hendry, D.F., 1992. "Forecasting in Cointegrated Systems," Economics Series Working Papers 99139, University of Oxford, Department of Economics.
  6. Víctor Gómez & Agustín Maravall, 1998. "Automatic Modeling Methods for Univariate Series," Banco de España Working Papers 9808, Banco de España.
  7. 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!]
  8. Víctor Gómez & Agustín Maravall, 1998. "Automatic Modeling Methods for Univariate Series," Banco de España Working Papers 9808, Banco de España.
  9. Granger, C W J & Newbold, P, 1973. "Some Comments on the Evaluation of Economic Forecasts," Applied Economics, Taylor and Francis Journals, vol. 5(1), pages 35-47, March.
  10. Bennett T. McCallum, 1991. "Targets, Indicators, and Instruments of Monetary Policy," NBER Working Papers 3047, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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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. Gabriel Moser & Fabio Rumler & Johann Scharler, 2004. "Forecasting Austrian Inflation," Working Papers 91, Oesterreichische Nationalbank (Austrian Central Bank). [Downloadable!]
    Other versions:
  2. Peter Vlaar & Ard den Reijer, 2004. "Forecasting inflation: An art as well as a science!," Computing in Economics and Finance 2004 148, Society for Computational Economics. [Downloadable!]
    Other versions:
  3. A.H.J. den Reijer & P.J.G. Vlaar, 2003. "Forecasting Inflation in the Netherlands and the Euro Area," WO Research Memoranda (discontinued) 723, Netherlands Central Bank, Research Department. [Downloadable!]
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