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Investigating Inflation Dynamics and Structural Change with an Adaptive ARFIMA Approach

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  • Richard T. Baille
  • Claudio Morana

Abstract

Previous models of monthly CPI inflation time series have focused on possible regime shifts, non-linearities and the feature of long memory. This paper proposes a new time series model, named Adaptive ARFIMA; which appears well suited to describe inflation and potentially other economic time series data. The Adaptive ARFIMA model includes a time dependent intercept term which follows a Flexible Fourier Form. The model appears to be capable of succesfully dealing with various forms of breaks and discontinities in the conditional mean of a time series. Simulation evidence justifies estimation by approximate MLE and model specfication through robust inference based on QMLE. The Adaptive ARFIMA model when supplemented with conditional variance models is found to provide a good representation of the G7 monthly CPI inflation series.

Suggested Citation

  • Richard T. Baille & Claudio Morana, 2009. "Investigating Inflation Dynamics and Structural Change with an Adaptive ARFIMA Approach," ICER Working Papers - Applied Mathematics Series 06-2009, ICER - International Centre for Economic Research.
    • Handle: RePEc:icr:wpmath:06-2009
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    References listed on IDEAS

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    Cited by:

    1. de Figueiredo, Erik Alencar, 2010. "Dynamics of regional unemployment rates in Brazil: Fractional behavior, structural breaks, and Markov switching," Economic Modelling, Elsevier, vol. 27(5), pages 900-908, September.

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    More about this item

    Keywords

    ARFIMA; FIGARCH; long memory; structural change; inflation; G7.;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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