Time-Varying Persistence of Inflation: Evidence from a Wavelet-Based Approach
Heni Boubaker (),
Rangan Gupta () and
Stephen Miller ()
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Heni Boubaker: IPAG LAB, IPAG Business School, France
No 201647, Working Papers from University of Pretoria, Department of Economics
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)
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-ets, nep-mac and nep-mon
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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:pre:wpaper:201647
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