A mover-stayer model with time-dependent stayer fraction
具有时变停留者比例的迁移者—停留者模型AI 解读 ↓
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具有时变停留者比例的迁移者—停留者模型
- 研究问题
- 个体是否永久停留不在基期固定，而可能随外生时变环境改变时，如何建模潜在迁移者、迁移者和停留者之间的动态转移？
- 方法与思路
- 作者以多项逻辑模型连接固定及外生时变协变量与状态转移概率，将初始状态和转入停留状态视为潜在变量，并采用极大似然估计。
- 材料陈述的贡献
- 摘要提出允许潜在迁移者随时间成为停留者的新模型，利用意大利学生跨大学流动面板说明应用，并通过模拟比较有限样本表现。
- 阅读关注点
- 应核对潜在状态的识别、进入停留状态的动态限制、时变协变量的外生性，以及似然计算和与传统模型比较的设定。
- 阅读边界
- 这是 arXiv 预印本，同行评审或接收状态未核实。摘要未说明识别条件、模拟结果和参数估计，不能把协变量关联解释为因果效应。
原文摘要
Mover-stayer models are used in social sciences and economics to model heterogeneous population dynamics in which some individuals never experience the event of interest ("stayers"), while others transition between states over time ("movers"). Conventionally, the mover-stayer status is determined at baseline and time-dependent covariates are only incorporated in the movers' transition probabilities. In this paper, we present a novel dynamic version of the mover-stayer model, allowing potential movers to become stayers over time based on time-varying circumstances. Using a multinomial logistic framework, our model incorporates both time-fixed and exogenous time-varying covariates to estimate transition probabilities among the states of potential movers, movers, and stayers. Both the initial state and transitions to the stayer state are treated as latent. The introduction of this new model is motivated by the study of student mobility. Specifically focusing on panel data on the inter-university mobility of Italian students, factors such as the students' change of course and university size are considered as time-varying covariates in modelling their probability of moving or becoming stayers; sex and age at enrolment as time-fixed covariates. We propose a maximum likelihood estimation approach and investigate its finite-sample performance through simulations, comparing it to established models in the literature.