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Bayesian Inference for the Mover-Stayer Model of Continuous Time

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Author Info

  • 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.

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Bibliographic Info

Paper provided by Toulouse - GREMAQ in its series Papers with number 98.b.

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Length: 36 pages
Date of creation: 1998
Date of revision:
Handle: RePEc:fth:gremaq:98.b

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Keywords: ANALYSE STATISTIQUE ; ECONOMETRIE ; MODELES ECONOMETRIQUES;

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Cited by:
  1. Michel Mouchart & Thierry Kamionka & Denis Fougère & Jean-Pierre Florens, 1994. "La modélisation économétrique des transitions individuelles sur le marché du travail," Économie et Prévision, Programme National Persée, vol. 116(5), pages 181-217.

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