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

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  • Jochmann, Markus

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.

Suggested Citation

  • Jochmann, Markus, 2010. "Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach," SIRE Discussion Papers 2010-06, Scottish Institute for Research in Economics (SIRE).
  • Handle: RePEc:edn:sirdps:139
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    File URL: http://hdl.handle.net/10943/139
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    References listed on IDEAS

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    1. Giordani, Paolo & Kohn, Robert & van Dijk, Dick, 2007. "A unified approach to nonlinearity, structural change, and outliers," Journal of Econometrics, Elsevier, vol. 137(1), pages 112-133, March.
    2. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
    3. Teh, Yee Whye & Jordan, Michael I. & Beal, Matthew J. & Blei, David M., 2006. "Hierarchical Dirichlet Processes," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1566-1581, December.
    4. Nelson, Charles R & Schwert, G William, 1977. "Short-Term Interest Rates as Predictors of Inflation: On Testing the Hypothesis That the Real Rate of Interest is Constant," American Economic Review, American Economic Association, vol. 67(3), pages 478-486, June.
    5. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
    6. Ang, Andrew & Bekaert, Geert, 2002. "Regime Switches in Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 163-182, April.
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    Citations

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    Cited by:

    1. repec:eee:intfor:v:33:y:2017:i:4:p:1025-1043 is not listed on IDEAS
    2. Mark Fisher & Mark J. Jensen, 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," Working Paper series 18-12, Rimini Centre for Economic Analysis.
    3. Luc Bauwens & Jean-François Carpantier & Arnaud Dufays, 2017. "Autoregressive Moving Average Infinite Hidden Markov-Switching Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 162-182, April.
    4. Yong Song, 2014. "Modelling Regime Switching And Structural Breaks With An Infinite Hidden Markov Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 825-842, August.
    5. Jin, Xin & Maheu, John M., 2016. "Bayesian semiparametric modeling of realized covariance matrices," Journal of Econometrics, Elsevier, vol. 192(1), pages 19-39.
    6. CARPANTIER, Jean-François & DUFAYS, Arnaud, 2014. "Specific Markov-switching behaviour for ARMA parameters," CORE Discussion Papers 2014014, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Fisher, Mark & Jensen, Mark J., 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," FRB Atlanta Working Paper 2018-2, Federal Reserve Bank of Atlanta.
    8. Maheu, John M. & Yang, Qiao, 2016. "An infinite hidden Markov model for short-term interest rates," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 202-220.
    9. Didier Nibbering & Richard Paap & Michel van der Wel, 2016. "A Bayesian Infinite Hidden Markov Vector Autoregressive Model," Tinbergen Institute Discussion Papers 16-107/III, Tinbergen Institute, revised 13 Oct 2017.
    10. repec:eee:streco:v:44:y:2018:i:c:p:23-33 is not listed on IDEAS
    11. Jean-François Carpantier, 2014. "Specific Markov-switching behaviour for ARMA parameters," CREA Discussion Paper Series 14-07, Center for Research in Economic Analysis, University of Luxembourg.

    More about this item

    Keywords

    inflation dynamics; hierarchical Dirichlet process; IHMM; structural breaks; Bayesian nonparametrics;

    JEL classification:

    • 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; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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