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Forecasting euro area inflation: Does contemponaneous aggregration improve the forecasting performance

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  • K. Hubrich

Abstract

Since price stability is the ESCB's primary objective, the evaluation of price development in the light of the second pillar of the ESCB's monetary policy strategy is essential. As the European Central Bank has started publishing its inflation forecast for the euro area in December 2000, forecasting inflation for the area has become of increasing importance. In this study it is systematically analysed whether the forecasting performance of euro area inflation models can be improved by aggregating forecasts of HICP subindices in comparison to forecasting total euro area inflation directly. The comparison is carried out across different methodological approaches. The VECM id found to ouperform the VAR and a univariate AR model for almost all HICP (sub-)indices. The results regarding the relative performance of aggregating forecasts of disaggregated time series in comparison with forecasting the aggregated time series directly, however, show a tendency for a better performance of forecasting euro area inflation directly. Therefore, relying on aggregated forecasts of subcomponents when forecasting euro area or national inflation should be considered with some caution.

Suggested Citation

  • K. Hubrich, 2001. "Forecasting euro area inflation: Does contemponaneous aggregration improve the forecasting performance," WO Research Memoranda (discontinued) 661, Netherlands Central Bank, Research Department.
  • Handle: RePEc:dnb:wormem:661
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    References listed on IDEAS

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    Cited by:

    1. Ard Reijer & Peter Vlaar, 2006. "Forecasting Inflation: An Art as Well as a Science!," De Economist, Springer, vol. 154(1), pages 19-40, March.
    2. Browne, Frank & Kelly, Robert, 2009. "Money and uncertainty in democratised financial markets," Research Technical Papers 16/RT/09, Central Bank of Ireland.
    3. Moser, Gabriel & Rumler, Fabio & Scharler, Johann, 2007. "Forecasting Austrian inflation," Economic Modelling, Elsevier, vol. 24(3), pages 470-480, May.
    4. 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).
    5. 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.

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