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相关随机系数模型的贝叶斯推断：因果效应异质性与教育回报AI 解读

We consider the problem of causal effect heterogeneity from a Bayesian point of view. This is accomplished by introducing a three-equation system, similar in spirit to the work of Heckman and Vytlacil (1998), describing the joint determination of a scalar outcome, an endogenous "treatment" variable, and an individual-specific causal return to that treatment. We describe a Bayesian posterior simulator for fitting this model which recovers far more than the average causal…

高中毕业与青年未来失业：来自High School and Beyond的新证据AI 解读

Abstract In this paper, I provide new evidence from High School and Beyond (HSB) on the effects of compulsory attendance on high school completion and future youth unemployment. I develop Bayesian estimation approaches to the simultaneous equation model with ordered probit and two‐limit censored regression and the bivariate duration model, accounting for the heterogeneity in returns to education and the nonlinearity in the effects of compulsory attendance. I find substantial…

辍学者会因辍学受损吗？广义选择模型中的结果增益估计与预测AI 解读

Abstract In this paper we describe methods for predicting distributions of outcome gains in the framework of a latent variable selection model. We describe such procedures for Student‐ t selection models and a finite mixture of Gaussian selection models. Importantly, our algorithms for fitting these models are simple to implement in practice, and also permit learning to take place about the non‐identified cross‐regime correlation parameter. Using data from High School and…