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

Listed author(s):
  • Heni Boubaker

    (IPAG Lab)

  • Giorgio Canarella

    (University of Nevada, Las Vegas)

  • Rangan Gupta

    (University of Pretoria)

  • Stephen M. Miller

    (University of Nevada, Las Vegas and University of Connecticut)

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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File URL: http://web2.uconn.edu/economics/working/2016-09.pdf
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Paper provided by University of Connecticut, Department of Economics in its series Working papers with number 2016-09.

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Length: 38 pages
Date of creation: Sep 2016
Handle: RePEc:uct:uconnp:2016-09
Note: Stephen Miller is the corresponding author
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University of Connecticut 365 Fairfield Way, Unit 1063 Storrs, CT 06269-1063

Phone: (860) 486-4889
Fax: (860) 486-4463
Web page: http://www.econ.uconn.edu/

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