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Structural Breaks in Inflation Dynamics within the European Monetary Union

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  • Thomas Windberger
  • Achim Zeileis

Abstract

To assess the effects of the EMU on inflation rate dynamics of its member states, the inflation rate series for 21 European countries are investigated for structural changes. To capture changes in mean, variance, and skewness of inflation rates, a generalized logistic model is adopted and complemented with structural break tests and breakpoint estimation techniques. These reveal considerable differences in the patterns of inflation dynamics and the structural changes therein. Overall, there is a convergence towards a lower mean inflation rate with reduced skewness, but it is accompanied by an increase in variance.

Suggested Citation

  • Thomas Windberger & Achim Zeileis, 2011. "Structural Breaks in Inflation Dynamics within the European Monetary Union," Working Papers 2011-12, Faculty of Economics and Statistics, Universität Innsbruck.
  • Handle: RePEc:inn:wpaper:2011-12
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    References listed on IDEAS

    as
    1. Caporale, Guglielmo Maria & Kontonikas, Alexandros, 2009. "The Euro and inflation uncertainty in the European Monetary Union," Journal of International Money and Finance, Elsevier, vol. 28(6), pages 954-971, October.
    2. Zeileis, Achim & Leisch, Friedrich & Hornik, Kurt & Kleiber, Christian, 2002. "strucchange: An R Package for Testing for Structural Change in Linear Regression Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i02).
    3. Achim Zeileis & Kurt Hornik, 2007. "Generalized M‐fluctuation tests for parameter instability," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 61(4), pages 488-508, November.
    4. Achim Zeileis, 2005. "A Unified Approach to Structural Change Tests Based on ML Scores, F Statistics, and OLS Residuals," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 445-466.
    5. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 127-152, April.
    6. J. Wilson Mixon Jr & Ryan J. Smith, 2006. "Teaching undergraduate econometrics with GRETL," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 1103-1107, November.
    7. Elena Andreou & Eric Ghysels, 2002. "Detecting multiple breaks in financial market volatility dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 579-600.
    8. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    9. Emerson, Michael & Gros, Daniel & Italianer, Alexander & ,, 1992. "One Market, One Money: An Evaluation of the Potential Benefits and Costs of Forming an Economic and Monetary Union," OUP Catalogue, Oxford University Press, number 9780198773245, Decembrie.
    10. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    11. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 169-177, April.
    12. Konstantinos Tolikas & Athanasios Koulakiotis & Richard A. Brown, 2007. "Extreme Risk and Value-at-Risk in the German Stock Market," The European Journal of Finance, Taylor & Francis Journals, vol. 13(4), pages 373-395.
    13. repec:bla:econom:v:55:y:1988:i:219:p:317-31 is not listed on IDEAS
    14. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    15. Patrick Lunnemann & Thomas Matha, 2009. "Mean reversion and sales," Applied Economics Letters, Taylor & Francis Journals, vol. 16(12), pages 1271-1275.
    16. Giulio Palomba & Emma Sarno & Alberto Zazzaro, 2009. "Testing similarities of short-run inflation dynamics among EU-25 countries after the Euro," Empirical Economics, Springer, vol. 37(2), pages 231-270, October.
    17. Hofmann, Boris & Remsperger, Hermann, 2005. "Inflation differentials among the Euro area countries: Potential causes and consequences," Journal of Asian Economics, Elsevier, vol. 16(3), pages 403-419, June.
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    Cited by:

    1. Daniela ZAPODEANU & Mihail Ioan COCIUBA & Sorina PETRIS, 2014. "The Inflation - Inflation Uncertainty Nexus In Romania," Journal of Public Administration, Finance and Law, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 0(Special i), pages 38-43, September.
    2. Christian Beer, 2011. "Literature Review on the Economic Effects of the Euro on Austria," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue 3, pages 22-34.

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    More about this item

    Keywords

    inflation rate; structural break; EMU; generalized logistic distribution;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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