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Multi-Factor Gegenbauer Processes and European Inflation Rates

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  • Guglielmo Maria Caporale
  • Luis A. Gil-Alana

Abstract

In this paper we specify a multi-factor long-memory process that enables us to estimate the fractional differencing parameters at each frequency separately, and adopt this framework to model quarterly prices in three European countries (France, Italy and the UK). The empirical results suggest that inflation in France and Italy is nonstationary. However, while for the former country this applies both to the zero and the seasonal frequencies, in the case of Italy the nonstationarity comes exclusively from the long-run or zero frequency. In the UK, inflation seems to be stationary with a component of long memory at both the zero and the semi-annual frequencies, especially at the former.

Suggested Citation

  • Guglielmo Maria Caporale & Luis A. Gil-Alana, 2009. "Multi-Factor Gegenbauer Processes and European Inflation Rates," Discussion Papers of DIW Berlin 879, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp879
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    References listed on IDEAS

    as
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    Cited by:

    1. Paul M. Beaumont & Aaron D. Smallwood, 2024. "Conditional sum of squares estimation of k-factor GARMA models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(3), pages 501-543, September.
    2. Asai Manabu & Peiris Shelton & McAleer Michael & Allen David E., 2020. "Cointegrated Dynamics for a Generalized Long Memory Process: Application to Interest Rates," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-18, January.
    3. Michael Funke & Marc Gronwald, 2009. "A Convex Hull Approach to Counterfactual Analysis of Trade Openness and Growth," Quantitative Macroeconomics Working Papers 20906, Hamburg University, Department of Economics.
    4. Beaumont, Paul & Smallwood, Aaron, 2019. "Inference for likelihood-based estimators of generalized long-memory processes," MPRA Paper 96313, University Library of Munich, Germany.
    5. M. Shelton Peiris & Manabu Asai, 2016. "Generalized Fractional Processes with Long Memory and Time Dependent Volatility Revisited," Econometrics, MDPI, vol. 4(3), pages 1-21, September.
    6. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Targeting: New Evidence from Fractional Integration and Cointegration," Working papers 2016-08, University of Connecticut, Department of Economics.
    7. Asai, M. & Peiris, S. & McAleer, M.J. & Allen, D.E., 2018. "Cointegrated Dynamics for A Generalized Long Memory Process," Econometric Institute Research Papers EI 2018-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Canarella, Giorgio & Miller, Stephen M., 2017. "Inflation targeting and inflation persistence: New evidence from fractional integration and cointegration," Journal of Economics and Business, Elsevier, vol. 92(C), pages 45-62.
    9. Beaumont, Paul & Smallwood, Aaron, 2019. "Conditional Sum of Squares Estimation of Multiple Frequency Long Memory Models," MPRA Paper 96314, University Library of Munich, Germany.

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    More about this item

    Keywords

    Fractional Integration; Long Memory; Inflation;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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