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Long-memory modeling and forecasting: evidence from the U.S. historical series of inflation

  • Heni Boubaker , Giorgio Canarella , Rangan Gupta and Stephen M. Miller EMAIL logo

Abstract

We report the results of applying several long-memory models to the historical monthly U.S. inflation rate series and analyze their out-of-sample forecasting performance over different horizons. We find that the time-varying approach to estimating inflation persistence outperforms the models that assume a constant long-memory process. In addition, we examine the link between inflation persistence and exchange rate regimes. Our results support the hypothesis that floating exchange rates associate with increased inflation persistence. This finding, however, is less pronounced during the era of the Great Moderation and the Federal Reserve System’s commitment to inflation targeting.

JEL Classification: C13; C22; C32; C54; E31

Corresponding author: Stephen M. Miller, University of Nevada, Las Vegas, 4505 S. Maryland Parkway, Las Vegas, Nevada, USA, E-mail

  1. Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

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Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/snde-2018-0116).


Received: 2018-12-05
Accepted: 2020-09-13
Published Online: 2020-10-26

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