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

Markus Jochmann

Research output: Working paperDiscussion paper

Abstract

This paper uses an infinite hidden Markov model (IHMM) 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.
LanguageEnglish
Place of PublicationGlasgow
PublisherUniversity of Strathclyde
Pages1-24
Number of pages25
Volume10
Publication statusPublished - Jan 2010

Fingerprint

Inflation dynamics
Modeling
Hidden Markov model
Structural breaks
Persistence
Financial crisis
Inflation persistence
Inflation

Keywords

  • inflation dynamics
  • hierarchical dirichlet process
  • ihmm
  • structural breaks
  • bayesian nonparametrics

Cite this

Jochmann, M. (2010). Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach. (01 ed.) (pp. 1-24). Glasgow: University of Strathclyde.
Jochmann, Markus. / Modeling U.S. Inflation Dynamics : A Bayesian Nonparametric Approach. 01. ed. Glasgow : University of Strathclyde, 2010. pp. 1-24
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Jochmann, M 2010 'Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach' 01 edn, University of Strathclyde, Glasgow, pp. 1-24.

Modeling U.S. Inflation Dynamics : A Bayesian Nonparametric Approach. / Jochmann, Markus.

01. ed. Glasgow : University of Strathclyde, 2010. p. 1-24.

Research output: Working paperDiscussion paper

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KW - bayesian nonparametrics

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Jochmann M. Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach. 01 ed. Glasgow: University of Strathclyde. 2010 Jan, p. 1-24.