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

Markus Jochmann ()

No 1001, Working Papers from University of Strathclyde Business School, Department of Economics

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.

Keywords: inflation dynamics; hierarchical Dirichlet process; IHMM; structural breaks; Bayesian nonparametrics (search for similar items in EconPapers)
JEL-codes: C11 C22 E31 (search for similar items in EconPapers)
Pages: 25 pages
Date: 2010-01
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.strath.ac.uk/media/1newwebsite/departme ... apers/2010/10-01.pdf (application/pdf)

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)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:str:wpaper:1001

Access Statistics for this paper

More papers in Working Papers from University of Strathclyde Business School, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Kirsty Hall ().