Working Paper

Bounding average treatment effects using linear programming

Authors

Lukáš Lafférs

Published Date

13 November 2015

Type

Working Paper (CWP70/15)

This paper presents a method of calculating sharp bounds on the average treatment effect using linear programming under identifying assumptions commonly used in the literature. This new method provides a sensitivity analysis of the identifying assumptions and missing data in an application regarding the effect of parent’s schooling on children’s schooling. Even a mild departure from identifying assumptions may substantially widen the bounds on average treatment effects. Allowing for a small fraction of the data to be missing also has a large impact on the results.