Time-Varying Persistence of Inflation: Evidence from a Wavelet-based Approach

Heni Boubaker (), Giorgio Canarella, Rangan Gupta and Stephen Miller

No 2016-09, Working papers from University of Connecticut, Department of Economics

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.

Keywords: Time-varying long-memory; LSTAR model; MODWT algorithm; ILSE estimator (search for similar items in EconPapers)
JEL-codes: C13 C22 C32 C54 E31 (search for similar items in EconPapers)
Pages: 38 pages
Date: 2016-09
New Economics Papers: this item is included in nep-cba, nep-ets, nep-mac and nep-mon
Note: Stephen Miller is the corresponding author
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Time-varying persistence of inflation: evidence from a wavelet-based approach (2017)
Working Paper: Time-Varying Persistence of Inflation: Evidence from a Wavelet-Based Approach (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:uct:uconnp:2016-09

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