Bounding average treatment effects using linear programming

Lukas Laffers

No 70/15, CeMMAP working papers from 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
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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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Persistent link: https://EconPapers.repec.org/RePEc:azt:cemmap:70/15

DOI: 10.1920/wp.cem.2015.7015

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