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Bayesian Inference for the Mover-Stayer Model of Continuous Time

Author

Listed:
  • Fougere, D.
  • Kamionka, T.

Abstract

This paper presents bayesian inference procedures for the continuous time mover-stayer model applied to individual transition data collected in discrete time. In particular, these methods allow to derive the probability of embeddability of the discrete-time modelling with the continuous-time one. A special emphasis is put on two alternative procedures, namely the importance of sampling and Gibbs sampling algorithms.

Suggested Citation

  • Fougere, D. & Kamionka, T., 1998. "Bayesian Inference for the Mover-Stayer Model of Continuous Time," Papers 98.b, Toulouse - GREMAQ.
  • Handle: RePEc:fth:gremaq:98.b
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    Cited by:

    1. Jean-Pierre Florens & Denis Fougère & Thierry Kamionka & Michel Mouchart, 1994. "La modélisation économétrique des transitions individuelles sur le marché du travail," Économie et Prévision, Programme National Persée, pages 181-217.
    2. Camilla Ferretti & Giampaolo Gabbi & Piero Ganugi & Pietro Vozzella, 2016. "Rating Trajectories and Credit Risk Migration: Evidence for SMEs," DISCE - Quaderni del Dipartimento di Scienze Economiche e Sociali dises1615, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    3. C. Ferretti & P. Ganugi, 2013. "A new mobility index for transition matrices," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(3), pages 403-425, August.

    More about this item

    Keywords

    ANALYSE STATISTIQUE ; ECONOMETRIE ; MODELES ECONOMETRIQUES;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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