Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach
AbstractThis 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.
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Bibliographic InfoPaper provided by Scottish Institute for Research in Economics (SIRE) in its series SIRE Discussion Papers with number 2010-06.
Date of creation: 2010
Date of revision:
inflation dynamics; hierarchical Dirichlet process; IHMM; structural breaks; Bayesian nonparametrics;
Other versions of this item:
- Markus Jochmann, 2010. "Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach," Working Papers 1001, University of Strathclyde Business School, Department of Economics.
- Markus Jochmann, 2010. "Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach," Working Paper Series 03_10, The Rimini Centre for Economic Analysis.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
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- Yong Song, 2012. "Modelling Regime Switching and Structural Breaks with an Infinite Hidden Markov Model," Working Paper Series 28_12, The Rimini Centre for Economic Analysis.
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