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Bayesian inference and state number determination for hidden Markov models: an application to the information content of the yield curve about inflation

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  • Chopin, Nicolas
  • Pelgrin, Florian

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  • Chopin, Nicolas & Pelgrin, Florian, 2004. "Bayesian inference and state number determination for hidden Markov models: an application to the information content of the yield curve about inflation," Journal of Econometrics, Elsevier, vol. 123(2), pages 327-344, December.
  • Handle: RePEc:eee:econom:v:123:y:2004:i:2:p:327-344
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    References listed on IDEAS

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    1. Walter R. Gilks & Carlo Berzuini, 2001. "Following a moving target-Monte Carlo inference for dynamic Bayesian models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(1), pages 127-146.
    2. Frederic S. Mishkin, 1990. "The Information in the Longer Maturity Term Structure about Future Inflation," The Quarterly Journal of Economics, Oxford University Press, vol. 105(3), pages 815-828.
    3. Goldfeld, Stephen M. & Quandt, Richard E., 1973. "A Markov model for switching regressions," Journal of Econometrics, Elsevier, vol. 1(1), pages 3-15, March.
    4. L. Wasserman, 2000. "Asymptotic inference for mixture models by using data-dependent priors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(1), pages 159-180.
    5. Jorion, Philippe & Mishkin, Frederic, 1991. "A multicountry comparison of term-structure forecasts at long horizons," Journal of Financial Economics, Elsevier, vol. 29(1), pages 59-80, March.
    6. Éric Jondeau & Roland Ricart, 1999. "Le contenu en information de la pente des taux : application au cas des titres publics français," Économie et Prévision, Programme National Persée, vol. 140(4), pages 1-20.
    7. Nicolas Chopin, 2001. "Sequential Inference and State Number Determination for Discrete State-Space Models through Particle Filtering," Working Papers 2001-34, Center for Research in Economics and Statistics.
    8. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    9. Kozicki, Sharon & Tinsley, P.A., 2005. "What do you expect? Imperfect policy credibility and tests of the expectations hypothesis," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 421-447, March.
    10. Fruhwirth-Schnatter S., 2001. "Markov Chain Monte Carlo Estimation of Classical and Dynamic Switching and Mixture Models," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 194-209, March.
    11. Tzavalis, Elias & Wickens, M. R., 1996. "Forecasting inflation from the term structure," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 103-122, May.
    12. Kim, Chang-Jin & Nelson, Charles R. & Startz, Richard, 1998. "Testing for mean reversion in heteroskedastic data based on Gibbs-sampling-augmented randomization1," Journal of Empirical Finance, Elsevier, vol. 5(2), pages 131-154, June.
    13. Robert J. Shiller & John Y. Campbell & Kermit L. Schoenholtz, 1983. "Forward Rates and Future Policy: Interpreting the Term Structure of Interest Rates," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 14(1), pages 173-224.
    14. Gerlach, Stefan, 1997. "The Information Content of the Term Structure: Evidence for Germany," Empirical Economics, Springer, vol. 22(2), pages 161-179.
    15. Nicolas Chopin, 2002. "A sequential particle filter method for static models," Biometrika, Biometrika Trust, vol. 89(3), pages 539-552, August.
    16. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    17. Hamilton, James D., 1996. "Specification testing in Markov-switching time-series models," Journal of Econometrics, Elsevier, vol. 70(1), pages 127-157, January.
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    Citations

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    Cited by:

    1. Gianni Amisano & Roberto Casarin, 2008. "Particle Filters for Markov-Switching Stochastic-Correlation Models," Working Papers 0814, University of Brescia, Department of Economics.
    2. Stéphane Adjemian & Florian Pelgrin, 2008. "Un regard bayésien sur les modèles dynamiques de la macroéconomie," Economie & Prévision, La Documentation Française, vol. 0(2), pages 127-152.
    3. repec:dau:papers:123456789/6830 is not listed on IDEAS
    4. Creal, D., 2009. "A survey of sequential Monte Carlo methods for economics and finance," Serie Research Memoranda 0018, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    5. He, Zhongfang & Maheu, John M., 2010. "Real time detection of structural breaks in GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2628-2640, November.
    6. Gary M. Koop & Simon M. Potter, 2004. "Forecasting and Estimating Multiple Change-point Models with an Unknown Number of Change-points," Discussion Papers in Economics 04/31, Department of Economics, University of Leicester.
    7. Sébastien Le Coent & Erwan Gautier & Benoît Bellone, 2006. "Les marchés financiers anticipent-ils les retournements conjoncturels ?," Économie et Prévision, Programme National Persée, vol. 172(1), pages 83-99.
    8. Sims, Christopher A. & Waggoner, Daniel F. & Zha, Tao, 2008. "Methods for inference in large multiple-equation Markov-switching models," Journal of Econometrics, Elsevier, vol. 146(2), pages 255-274, October.
    9. Christopher Nam & John Aston & Adam Johansen, 2014. "Parallel sequential Monte Carlo samplers and estimation of the number of states in a Hidden Markov Model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(3), pages 553-575, June.
    10. 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.
    11. Matthieu Lemoine & Florian Pelgrin, 2003. "Introduction aux modèles espace-état et au filtre de Kalman," Revue de l'OFCE, Presses de Sciences-Po, vol. 86(3), pages 203-229.
    12. Nicolas Chopin, 2007. "Dynamic Detection of Change Points in Long Time Series," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 59(2), pages 349-366, June.

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