Bounding average treatment effects using linear programming

No CWP70/15, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: 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.

Date: 2015-11-13
New Economics Papers: this item is included in nep-ecm
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Related works:
Journal Article: Bounding average treatment effects using linear programming (2019)
Working Paper: Bounding average treatment effects using linear programming (2015)
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