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Measures of Underlying Inflation in the Euro Area; Assessment and Role for Informing Monetary Policy

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  • Emil Stavrev

Abstract

The paper evaluates the 24-month ahead inflation forecasting performance of various indicators of underlying inflation and structural models. The inflation forecast errors resulting from model misspecification are larger than the errors resulting from forecasting of exogenous variables. Also, measures derived using the generalized dynamic factor model (GDFM) overperform other measures over the monetary policy horizon and are leading indicators of headline inflation. Trimmed means, although weaker than GDFM indicators, have good forecasting performance, while indicators by permanent exclusion underperform but provide useful information about short-term dynamics. The forecasting performance of theoretically-founded models that relate monetary aggregates, the output gap, and inflation improves with the time horizon but generally falls short of that of the GDFM. A composite measure of underlying inflation, derived by averaging the statistical indicators and the model-based estimates, improves forecast accuracy by eliminating bias and offers valuable insight about the distribution of risks.

Suggested Citation

  • Emil Stavrev, 2006. "Measures of Underlying Inflation in the Euro Area; Assessment and Role for Informing Monetary Policy," IMF Working Papers 06/197, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:06/197
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    References listed on IDEAS

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    1. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 830-840, September.
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    Citations

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    Cited by:

    1. Claudiu Tiberiu Albulescu & Daniel Goyeau & Cornel Oros, 2015. "On the Long Run Money-Prices Relationship in CEE Countries," Economic Research Guardian, Weissberg Publishing, vol. 5(1), pages 73-96, June.
    2. Emil Stavrev & Helge Berger, 2012. "The information content of money in forecasting euro area inflation," Applied Economics, Taylor & Francis Journals, vol. 44(31), pages 4055-4072, November.
    3. Berger, Helge & Harjes, Thomas & Stavrev, Emil, 2008. "The ECB's monetary analysis revisited," Discussion Papers 2008/14, Free University Berlin, School of Business & Economics.
    4. Sandra Eickmeier & Christina Ziegler, 2008. "How successful are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 237-265.
    5. Gatt, William, 2014. "An evaluation of core inflation measures for Malta," MPRA Paper 61250, University Library of Munich, Germany.

    More about this item

    Keywords

    Euro Area; Economic models; Monetary policy; Inflation; Underlying inflation; forecast evaluation; composite indicators; forecast risk assessment; monetary aggregates; inflation dynamics; central bank; Model Construction and Estimation; Model Evaluation and Selection; Forecasting and Other Model Applications;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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