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A Factor Model for Euro-area Short-term Inflation Analysis

Author

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  • Lenza Michele

    (European Central Bank, DG Research/Econometric Modelling Division, Kaiserstrasse 29, 60311 Frankfurt a.M., Germany)

  • Warmedinger Thomas

    (European Central Bank, DG Economics/Fiscal Policy Division, Kaiserstrasse 29, 60311 Frankfurt a.M., Germany)

Abstract

This paper develops a factor model for forecasting inflation in the euro area. The model can handle variables with different timeliness, sample size and frequency. We show that the forecasts based on the factor model outperform naïve random walk forecasts, a hard to beat benchmark for euro area inflation forecasts in recent years, at horizons of and beyond nine months ahead. They are also comparable, in terms of accuracy, to the judgemental forecasts prepared in the context of the Eurosystem macroeconomic projection exercises. The factor model is therefore a very suitable tool to extract the signal on current and future euro area inflation from new data releases.

Suggested Citation

  • Lenza Michele & Warmedinger Thomas, 2011. "A Factor Model for Euro-area Short-term Inflation Analysis," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 50-62, February.
  • Handle: RePEc:jns:jbstat:v:231:y:2011:i:1:p:50-62
    DOI: 10.1515/jbnst-2011-0105
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    References listed on IDEAS

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    Cited by:

    1. Zivile Zekaite & Gabe de Bondt & Elke Hahn, 2017. "Alice: A New Inflation Monitoring Tool," EcoMod2017 10414, EcoMod.
    2. Fröhling, Annette & Lommatzsch, Kirsten, 2011. "Output sensitivity of inflation in the euro area: Indirect evidence from disaggregated consumer prices," Discussion Paper Series 1: Economic Studies 2011,25, Deutsche Bundesbank.
    3. Siliverstovs Boriss & Kholodilin Konstantin A., 2012. "Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP: Evidence for Switzerland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(4), pages 429-444, August.
    4. Modugno, Michele, 2013. "Now-casting inflation using high frequency data," International Journal of Forecasting, Elsevier, vol. 29(4), pages 664-675.
    5. de Bondt, Gabe J. & Hahn, Elke & Zekaite, Zivile, 2021. "ALICE: Composite leading indicators for euro area inflation cycles," International Journal of Forecasting, Elsevier, vol. 37(2), pages 687-707.

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