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Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?

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  • Hubrich, Kirstin

Abstract

Monitoring and forecasting price developments in the euro area is essential in the light of the second pillar of the ECB's monetary policy strategy. This study analyses whether the forecasting accuracy of forecasting aggregate euro area inflation can be improved by aggregating forecasts of subindices of the Harmonized Index of Consumer Prices (HICP) as opposed to forecasting the aggregate HICP directly. The analysis includes univariate and multivariate linear time series models and distinguishes between different forecast horizons, HICP components and inflation measures. Various model selection procedures are employed to select models for the aggregate and the disaggregate components. The results indicate that aggregating forecasts by component does not necessarily help forecast year-on-year inflation twelve months ahead. JEL Classification: E31, E37, C53, C32

Suggested Citation

  • Hubrich, Kirstin, 2003. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," Working Paper Series 247, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:2003247
    Note: 1325881
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    More about this item

    Keywords

    euro area inflation; HICP subindex forecast aggregation; linear time series models;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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