Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/130074
Authors: 
Lafférs, Lukáés
Year of Publication: 
2015
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP70/15
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.
Subjects: 
Partial identification
Bounds
Average treatment effect
Sensitivity analysis
JEL: 
C4
C6
I2
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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