Time-varying persistence of inflation : evidence from a wavelet-based approach

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Authors

Boubaker, Heni
Canarella, Giorgio
Gupta, Rangan
Miller, Stephen M.

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Volume Title

Publisher

De Gruyter

Abstract

We propose a new long-memory model with a time-varying fractional integration parameter, evolving non-linearly according to a Logistic Smooth Transition Autoregressive (LSTAR) specification. To estimate the time-varying fractional integration parameter, we implement a method based on the wavelet approach, using the instantaneous least squares estimator (ILSE). The empirical results show the relevance of the modeling approach and provide evidence of regime change in inflation persistence that contributes to a better understanding of the inflationary process in the US. Most importantly, these empirical findings remind us that a "one-size-fits-all" monetary policy is unlikely to work in all circumstances.

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Keywords

Time-varying long-memory, LSTAR model, MODWT algorithm, Logistic smooth transition autoregressive (LSTAR), Instantaneous least squares estimator (ILSE), Maximum overlap discrete wavelet transform (MODWT)

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Citation

Boubaker, H., Canarella, G., Gupta, R. & Miller, S.M. 2017, 'Time-varying persistence of inflation : evidence from a Wavelet-based approach', Studies in Nonlinear Dynamics and Econometrics, vol. 21, no. 4, pp. 1-38.