全球智库信息集成服务系统(G2TT): The Causal Interpretation of Two-Stage Least Squares with Multiple Instrumental Variables

G2TT

来源类型	Working Paper
规范类型	报告
DOI	10.3386/w25691
来源ID	Working Paper 25691
	The Causal Interpretation of Two-Stage Least Squares with Multiple Instrumental Variables
	Magne Mogstad; Alexander Torgovitsky; Christopher R. Walters
发表日期	2019-03-25
出版年	2019
语种	英语
摘要	Empirical researchers often combine multiple instrumental variables (IVs) for a single treatment using two-stage least squares (2SLS). When treatment effects are heterogeneous, a common justification for including multiple IVs is that the 2SLS estimand can be given a causal interpretation as a positively-weighted average of local average treatment effects (LATEs). This justification requires the well-known monotonicity condition. However, we show that with more than one instrument, this condition can only be satisfied if choice behavior is effectively homogenous. Based on this finding, we consider the use of multiple IVs under a weaker, partial monotonicity condition. We characterize empirically verifiable sufficient and necessary conditions for the 2SLS estimand to be a positively-weighted average of LATEs under partial monotonicity. We apply these results to an empirical analysis of the returns to college with multiple instruments. We show that the standard monotonicity condition is at odds with the data. Nevertheless, our empirical checks show that the 2SLS estimate retains a causal interpretation as a positively-weighted average of the effects of college attendance among complier groups.
主题	Econometrics ; Estimation Methods
URL	https://www.nber.org/papers/w25691
来源智库	National Bureau of Economic Research (United States)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/583364
推荐引用方式 GB/T 7714	Magne Mogstad,Alexander Torgovitsky,Christopher R. Walters. The Causal Interpretation of Two-Stage Least Squares with Multiple Instrumental Variables. 2019.

条目包含的文件
文件名称/大小	资源类型	版本类型	开放类型	使用许可
w25691.pdf（768KB）	智库出版物		限制开放	CC BY-NC-SA	浏览