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Forecasting Austrian Inflation

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Author Info
Gabriel Moser () (Oesterreichische Nationalbank, Foreign Research Department, Otto-Wagner Platz 3, POB 61, A-1011 Vienna)
Fabio Rumler () (Oesterreichische Nationalbank, Economic Analysis Division)
Johann Scharler () (Oesterreichische Nationalbank, Economic Analysis Division)

Additional information is available for the following registered author(s):

Abstract

In this paper we apply factor models proposed by Stock and Watson [18] and VAR and ARIMA models to generate 12-month out of sample forecasts of Austrian HICP inflation and its subindices processed food, unprocessed food, energy, industrial goods and services price inflation. A sequential forecast model selection procedure tailored to this specific task is applied. It turns out that factor models possess the highest predictive accuracy for several subindices and that predictive accuracy can be further improved by combining the information contained in factor and VAR models for some indices. With respect to forecasting HICP inflation, our analysis suggests to favor the aggregation of subindices forecasts. Furthermore, the subindices forecasts are used as a tool to give a more detailed picture of the determinants of HICP inflation from both an ex-ante and ex-post perspective.

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Publisher Info
Paper provided by Oesterreichische Nationalbank (Austrian Central Bank) in its series Working Papers with number 91.

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Length: 52 pages
Date of creation: 04 Oct 2004
Date of revision:
Handle: RePEc:onb:oenbwp:91

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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: Inflation Forecasting Forecast Model selection Aggregation

Other versions of this item:

Find related papers by JEL classification:
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
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. Todd E. Clark & Michael W. McCracken, 2001. "Evaluating long-horizon forecasts," Research Working Paper RWP 01-14, Federal Reserve Bank of Kansas City. [Downloadable!]
  2. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December. [Downloadable!] (restricted)
  3. Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers 0192, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  4. Kunst, Robert M., 2003. "Testing for Relative Predictive Accuracy: A Critical Viewpoint," Economics Series 130, Institute for Advanced Studies. [Downloadable!]
  5. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  6. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June. [Downloadable!] (restricted)
  7. 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:
  8. Ashley, Richard, 2003. "Statistically significant forecasting improvements: how much out-of-sample data is likely necessary?," International Journal of Forecasting, Elsevier, vol. 19(2), pages 229-239. [Downloadable!] (restricted)
  9. 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!]
  10. 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!]
  11. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-59, April.
  12. Elena Angelini & Jerome Henry & Ricardo Mestre, 2001. "Diffusion index-based inflation forecasts for the euro area," Working Paper Series 061, European Central Bank. [Downloadable!]
  13. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
    Other versions:
  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). [Downloadable!]
  15. Massimiliano Marcellino & James H. Stock & Mark W. Watson, . "Macroeconomic Forecasting in the Euro Area: Country Specific versus Area-Wide Information," Working Papers 201, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University. [Downloadable!]
    Other versions:
  16. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January. [Downloadable!] (restricted)
    Other versions:
Full references

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. Janine Aron & John Muellbauer, . "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!]
  2. Roman Horvath, 2007. "The Time-Varying Policy Neutral Rate in Real Time: A Predictor for Future Inflation?," Working Papers 2007/4, Czech National Bank, Research Department. [Downloadable!]
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