Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach

Markus Jochmann ()

No 2010-06, SIRE Discussion Papers from Scottish Institute for Research in Economics (SIRE)

Abstract: This paper uses an infinite hidden Markov model (IIHMM) to analyze U.S. inflation dynamics with a particular focus on the persistence of inflation. The IHMM is a Bayesian nonparametric approach to modeling structural breaks. It allows for an unknown number of breakpoints and is a flexible and attractive alternative to existing methods. We found a clear structural break during the recent financial crisis. Prior to that, inflation persistence was high and fairly constant.

Keywords: inflation dynamics; hierarchical Dirichlet process; IHMM; structural breaks; Bayesian nonparametrics (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach (2015)
Working Paper: Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach (2010)
Working Paper: Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:edn:sirdps:139

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