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A structural common factor approach to core inflation estimation and forecasting


  • Claudio Morana


In the article we propose a new methodological approach to core inflation estimation, based on a frequency domain principal components estimator, suited to estimate systems of fractionally co-integrated processes. The proposed core inflation measure is the common persistent feature in inflation and excess nominal money growth and bears the interpretation of monetary inflation. The proposed measure is characterized by all the properties that an 'ideal' core inflation process should show, providing also a superior forecasting performance relative to other available measures.

Suggested Citation

  • Claudio Morana, 2007. "A structural common factor approach to core inflation estimation and forecasting," Applied Economics Letters, Taylor & Francis Journals, vol. 14(3), pages 163-169.
  • Handle: RePEc:taf:apeclt:v:14:y:2007:i:3:p:163-169 DOI: 10.1080/13504850500425147

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    References listed on IDEAS

    1. Elena Angelini & Jérôme Henry & Ricardo Mestre, 2001. "Diffusion index-based inflation forecasts for the euro area," BIS Papers chapters,in: Bank for International Settlements (ed.), Empirical studies of structural changes and inflation, volume 3, pages 109-138 Bank for International Settlements.
    2. Fabio Bagliano & Roberto Golinelli & Claudio Morana, 2002. "Core inflation in the Euro area," Applied Economics Letters, Taylor & Francis Journals, vol. 9(6), pages 353-357.
    3. Elena Angelini & Jérôme Henry & Ricardo Mestre, 2001. "A multi-country trend indicator for euro area inflation: computation and properties," BIS Papers chapters,in: Bank for International Settlements (ed.), Empirical studies of structural changes and inflation, volume 3, pages 81-108 Bank for International Settlements.
    4. Christopher F. Baum & John T. Barkoulas & Mustafa Caglayan, 1999. "Persistence in International Inflation Rates," Southern Economic Journal, Southern Economic Association, vol. 65(4), pages 900-913, April.
    5. repec:cup:etheor:v:13:y:1997:i:3:p:315-52 is not listed on IDEAS
    6. Bai, Jushan, 1997. "Estimating Multiple Breaks One at a Time," Econometric Theory, Cambridge University Press, vol. 13(03), pages 315-352, June.
    7. Ang, Andrew & Bekaert, Geert, 2002. "Regime Switches in Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 163-182, April.
    8. Baillie, Richard T & Chung, Ching-Fan & Tieslau, Margie A, 1996. "Analysing Inflation by the Fractionally Integrated ARFIMA-GARCH Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(1), pages 23-40, Jan.-Feb..
    9. Fabio C. Bagliano & Claudio Morana, 1999. "Measuring Core Inflation in Italy," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 58(3-4), pages 301-328, December.
    10. Arrazola, Maria & de Hevia, Jose, 2002. "An alternative measure of core inflation," Economics Letters, Elsevier, vol. 75(1), pages 69-73, March.
    11. Fabio C. Bagliano & Claudio Morana, 2003. "A common trends model of UK core inflation," Empirical Economics, Springer, vol. 28(1), pages 157-172, January.
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    Cited by:

    1. Wojciech Charemza & Imran Husssain Shah, 2013. "Stability price index, core inflation and output volatility," Applied Economics Letters, Taylor & Francis Journals, vol. 20(8), pages 737-741, May.
    2. Ascari, Guido & Rankin, Neil, 2007. "Perpetual youth and endogenous labor supply: A problem and a possible solution," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 708-723, December.
    3. Franz Ruch & Mehmet Balcilar & Mampho P. Modise & Rangan Gupta, 2015. "Forecasting Core Inflation: The Case of South Africa," Working Papers 201543, University of Pretoria, Department of Economics.
    4. Baillie, Richard T. & Morana, Claudio, 2012. "Adaptive ARFIMA models with applications to inflation," Economic Modelling, Elsevier, vol. 29(6), pages 2451-2459.
    5. Cavallero, Alessandro, 2011. "The convergence of inflation rates in the EU-12 area: A distribution dynamics approach," Journal of Macroeconomics, Elsevier, vol. 33(2), pages 341-357, June.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy


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