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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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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 123 (2004)
Issue (Month): 2 (December)
Pages: 327-344

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Handle: RePEc:eee:econom:v:123:y:2004:i:2:p:327-344

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Web page: http://www.elsevier.com/locate/jeconom

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  1. Sharon Kozicki & P.A.Tinsley, 2001. "What do you expect? : imperfect policy credibility and tests of the expectations hypothesis?," Research Working Paper RWP 01-02, Federal Reserve Bank of Kansas City.
  2. Gerlach, Stefan, 1997. "The Information Content of the Term Structure: Evidence for Germany," Empirical Economics, Springer, vol. 22(2), pages 161-79.
  3. 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.
  4. 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.
  5. 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 357-84, March.
  6. Goldfeld, Stephen M. & Quandt, Richard E., 1973. "A Markov model for switching regressions," Journal of Econometrics, Elsevier, vol. 1(1), pages 3-15, March.
  7. Nicolas Chopin, 2000. "A Sequential Particle Filter Method for Static Models," Working Papers 2000-45, Centre de Recherche en Economie et Statistique.
  8. Nicolas Chopin, 2001. "Sequential Inference and State Number Determination for Discrete State-Space Models through Particle Filtering," Working Papers 2001-34, Centre de Recherche en Economie et Statistique.
  9. 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.
  10. Jondeau, E. & Ricart, R., 1997. "Le contenu en information de la pente des taux : application au cas des titres publics français," Working papers 43, Banque de France.
  11. Robert J. Shiller & John Y. Campbell & Kermit L. Schoenholtz, 1983. "Forward Rates and Future Policy: Interpreting the Term Structure of Interest Rates," Cowles Foundation Discussion Papers 667, Cowles Foundation for Research in Economics, Yale University.
  12. 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.
  13. Frederic S. Mishkin, 1991. "The Information in the Longer Maturity Term Structure about Future Inflation," NBER Working Papers 3126, National Bureau of Economic Research, Inc.
  14. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
  15. Tzavalis, E. & Wickens, M.R., 1995. "Forecasting Inflation from the Term Structure," Discussion Papers 9519, Exeter University, Department of Economics.
  16. Hamilton, James D., 1996. "Specification testing in Markov-switching time-series models," Journal of Econometrics, Elsevier, vol. 70(1), pages 127-157, January.
  17. 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.
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Citations

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Cited by:
  1. Zhongfang He & John M Maheu, 2008. "Real Time Detection of Structural Breaks in GARCH Models," Working Papers tecipa-336, University of Toronto, Department of Economics.
  2. Casarin, Roberto & Trecroci, Carmine, 2006. "Business Cycle and Stock Market Volatility: A Particle Filter Approach," Economics Papers from University Paris Dauphine 123456789/6830, Paris Dauphine University.
  3. 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.
  4. 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.
  5. 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, vol. 66(3), pages 553-575, June.
  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. Gianni Amisano & Roberto Casarin, 2008. "Particle Filters for Markov-Switching Stochastic-Correlation Models," Working Papers 0814, University of Brescia, Department of Economics.
  8. Nicolas Chopin, 2007. "Dynamic Detection of Change Points in Long Time Series," Annals of the Institute of Statistical Mathematics, Springer, vol. 59(2), pages 349-366, June.
  9. Stéphane Adjemian & Florian Pelgrin, 2008. "Un regard bayésien sur les modèles dynamiques de la macroéconomie," Économie et Prévision, Programme National Persée, vol. 183(2), pages 127-152.
  10. Tsasa Vangu, Jean-Paul Kimbambu, 2014. "Diagnostic de la politique monétaire en Rép. Dém. Congo – Approche par l’Equilibre Général Dynamique Stochastique," Dynare Working Papers 38, CEPREMAP.
  11. 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.

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