Bayesian Inference for the Mover-Stayer Model of Continuous Time.

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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Year of publication:	1998
Authors:	Fougere, D. ; Kamionka, T.
Institutions:	Groupe de Recherche en Économie Mathématique et Quantitative (GREMAQ), Toulouse School of Economics (TSE)
Subject:	ANALYSE STATISTIQUE \| ECONOMETRIE \| MODELES ECONOMETRIQUES

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Series:	Toulouse - GREMAQ.
Type of publication:	Book / Working Paper
Notes:	36 pages
Classification:	C10 - Econometric and Statistical Methods: General. General ; C11 - Bayesian Analysis ; C50 - Econometric Modeling. General
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005639406