标题:Nonparametric identification and estimation of dynamic treatment effects for survival data in a regression discontinuity design
作者:Lv, Xiaofeng; Sun, Xu-Ran; Lu, Yue; Li, Rui
作者机构:[Lv, Xiaofeng] Southwestern Univ Finance & Econ, Sch Int Business, Chengdu, Sichuan, Peoples R China.; [Sun, Xu-Ran] Shandong Univ, Ctr Econ Res, Ji 更多
通讯作者:Li, R
通讯作者地址:[Li, R]Beijing Normal Univ, Business Sch, Beijing, Peoples R China.
来源:ECONOMICS LETTERS
出版年:2019
卷:184
DOI:10.1016/j.econlet.2019.108665
关键词:Nonparametric identification; Treatment effects; Regression; discontinuity; Survival analysis; Dynamic treatment assignment
摘要:Treatment assignment in the survival literature is often assumed to be allocated simultaneously and independently of prospective treatment gains. This paper relaxes these restrictions by introducing dynamic treatment assignment for survival data in a regression discontinuity design. Conditional on a pretreatment duration, we identify two survival functions of the remaining potential durations under treatment and no treatment. Conditional treatment effects can be identified by the difference between the integrals of the two functions, and we aggregate conditional treatment effects over pretreatment durations to identify unconditional ones. Accordingly, nonparametric estimates are proposed. (C) 2019 Elsevier B.V. All rights reserved.
收录类别:SCOPUS;SSCI
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071890464&doi=10.1016%2fj.econlet.2019.108665&partnerID=40&md5=7ba7929a1ec4f2bc2ae56012d5124198
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