回归不连续设计
收益
贝叶斯概率
间断(语言学)
经济
计量经济学
政府(语言学)
模糊逻辑
回归
统计
计算机科学
数学
财务
人工智能
语言学
数学分析
哲学
作者
Siddhartha Chib,Liana Jacobi
摘要
Summary This paper is concerned with the use of a Bayesian approach to fuzzy regression discontinuity (RD) designs for understanding the returns to education. The discussion is motivated by the change in government policy in the UK in April of 1947, when the minimum school leaving age was raised from 14 to 15—a change that had a discontinuous impact on the probability of leaving school at age 14 for cohorts who turned 14 around the time of the policy change. We develop a Bayesian fuzzy RD framework that allows us to take advantage of this discontinuity to calculate the effect of an additional year of education on subsequent log earnings for the (latent) class of subjects that complied with the policy change. We illustrate this approach with a new dataset composed from the UK General Household Surveys. Copyright © 2015 John Wiley & Sons, Ltd.
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