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【12月19日】Bayesian Inference in a Correlated R

题目:Bayesian Inference in a Correlated Random Coefficients Model: Modeling Treatment Effect Heterogeneity and Heterogeneous Returns to Schooling

演讲人:黎明亮 美国纽约州立大学布法罗分校经济学助教授

时间:2008年12月19日,周五,  14:00-15:30

地点:上海交通大学北楼101

演讲内容简介:We consider the problem of treatment 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 return to treatment. We describe a Bayesian posterior simulator for fitting this model which recovers far more than the average return to treatment in the population, the object which has been the focus of most previous work. Parameter identification and generalized methods for flexibly modeling the outcome and return heterogeneity distributions are also discussed. Combining data sets from High School and Beyond (HSB) and the 1980 Census, we illustrate our methods in practice and investigate heterogeneity in returns to education. Our analysis decomposes the impact of key HSB covariates on log wages into three parts: a “direct" effect and two separate indirect effects through educational attainment and returns to education. Our results suggest strong evidence that the quantity of schooling attained is determined, in part, by the individual’s own return to education. Specifically, a one percentage increase in the return to schooling parameter is associated with the receipt of (approximately) .2 more years of education.

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