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连续时间流动者—留驻者模型的贝叶斯推断及劳动市场转移应用AI 解读

Abstract This paper presents Bayesian inference procedures for the continuous time mover–stayer model applied to labour market transition data collected in discrete time. These methods allow us 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 sampling algorithm and a new Gibbs sampling algorithm. Transition intensities, proportions of stayers…

转移模型中的模拟最大似然估计AI 解读

In this paper we analyse the problem of modelling individual transitions in the presence of an incomplete sampling scheme. This problem is particularly cumbersome when a continuous time-scale is used for the modelling and when the model incorporates unobserved heterogeneity. This problem arises, for instance, when the observation is made at fixed time points or stops on an interval of time. In order to take this phenomenon into account, we propose to maximize the simulated…