A0516
Title: Assessing heterogeneity in treatment effects
Authors: Tetsuya Kaji - University of Chicago (United States) [presenting]
Jianfei Cao - Northeastern University (United States)
Abstract: Treatment heterogeneity is of significant concern in economics, but the lack of identification of the joint distribution of the treated and control outcomes hinders its assessment. For example, the effect of having insurance on the health of otherwise unhealthy individuals may need to be assessed, but it is often infeasible to ensure only the unhealthy ones, and thus the causal effects for those are not identified. , here may be interested in the shares of winners and losers from a minimum wage increase, but the shares are not identified without the joint distribution. It is shown that these quantities are partially identified and derive tight bounds that complement quantile treatment effects.
