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Nonparametric modeling for the time-varying persistence of inflation

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  • Yu, Deshui
  • Chen, Li
  • Li, Luyang

Abstract

This article develops a novel nonparametric time-varying auto-regressive distributed lag model to estimate the persistence of inflation. The local linear estimation method is used to estimate the coefficients. Empirically, the persistence of the inflation process in the United States declined prior to the global financial crisis (GFC) of 2007–2009, but then rebounded strongly until 2022.

Suggested Citation

  • Yu, Deshui & Chen, Li & Li, Luyang, 2023. "Nonparametric modeling for the time-varying persistence of inflation," Economics Letters, Elsevier, vol. 225(C).
    • Handle: RePEc:eee:ecolet:v:225:y:2023:i:c:s0165176523000654
    DOI: 10.1016/j.econlet.2023.111040
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    References listed on IDEAS

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    More about this item

    Keywords

    Inflation persistence; Time-varying coefficient model; Locally stationary process; Local linear estimation;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric 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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