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

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  • Mr. 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

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

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    Cited by:

    1. Mr. Helge Berger & Mr. Thomas Harjes & Mr. Emil Stavrev, 2008. "The ECB’s Monetary Analysis Revisited," IMF Working Papers 2008/171, International Monetary Fund.
    2. 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.
    3. 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.
    4. Berger, Helge & Harjes, Thomas & Stavrev, Emil, 2008. "The ECB's monetary analysis revisited," Discussion Papers 2008/14, Free University Berlin, School of Business & Economics.
    5. 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.
    6. Liam J. A. Lenten, 2010. "Bananas and petrol: further evidence on the forecasting accuracy of the ABS 'headline' and 'underlying' rates of inflation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(6), pages 556-572.
    7. Gatt, William, 2014. "An evaluation of core inflation measures for Malta," MPRA Paper 61250, University Library of Munich, Germany.
    8. Mr. Emil Stavrev & Mr. Helge Berger, 2008. "The Information Content of Money in Forecasting Euro Area Inflation," IMF Working Papers 2008/166, International Monetary Fund.

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