Direct and indirect treatment effects-causal chains and mediation analysis with instrumental variables

• 成果类型: Article
• 署名作者: Froelich, Markus; Huber, Martin
• 署名单位: University of Mannheim; University of Fribourg
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1111/rssb.12260
• 发表日期: 2017
• 页码: 1645-1666
• 关键词: identification; average; endogeneity; mechanisms; inference; education; designs; HEALTH

摘要

The paper discusses the non-parametric identification of causal direct and indirect effects of a binary treatment based on instrumental variables. We identify the indirect effect, which operates through a mediator (i.e. intermediate variable) that is situated on the causal path between the treatment and the outcome, as well as the unmediated direct effect of the treatment by using distinct instruments for the endogenous treatment and the endogenous mediator. We examine various settings to obtain non-parametric identification of (natural) direct and indirect as well as controlled direct effects for continuous and discrete mediators and continuous and discrete instruments. We also provide a simulation study and two empirical illustrations.