Testing treatment effect heterogeneity in regression discontinuity designs

被引：15

作者：

Hsu, Yu-Chin ^{[1
,2
,3
,5
]}

Shen, Shu ^{[4
]}

机构：

[1] Acad Sinica, Inst Econ, Taipei, Taiwan

[2] Natl Cent Univ, Dept Finance, Taoyuan, Taiwan

[3] Natl Chengchi Univ, Dept Econ, Taipei, Taiwan

[4] Univ Calif Davis, Dept Econ, One Shields Ave, Davis, CA 95616 USA

[5] 128 Acad Rd,Sect 2, Taipei 115, Taiwan

来源：

JOURNAL OF ECONOMETRICS | 2019年 / 208卷 / 02期

关键词：

Sharp regression discontinuity; Fuzzy regression discontinuity; Treatment effect heterogeneity; INFERENCE;

D O I：

10.1016/j.jeconom.2018.10.004

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

Treatment effect heterogeneity is frequently studied in regression discontinuity (RD) applications. This paper proposes, under the RD setup, formal tests for treatment effect heterogeneity among individuals with different observed pre-treatment characteristics. The proposed tests study whether a policy treatment (1) is beneficial for at least some subpopulations defined by pre-treatment covariate values, (2) has any impact on at least some subpopulations, and (3) has a heterogeneous impact across subpopulations. The empirical section applies the tests to study the impact of attending a better high school and discovers interesting patterns of treatment effect heterogeneity neglected by previous studies. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：468 / 486

页数：19

共 44 条

[1] Multiple Inference and Gender Differences in the Effects of Early Intervention: A Reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects [J].