Identifying effects of multivalued treatments
Sokbae (Simon) Lee () and
Bernard Salanié ()
No CWP34/18, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies
Multivalued treatment models have typically been studied under restrictive assumptions: ordered choice, and more recently unordered monotonicity. We show how treatment effects can be identi fied in a more general class of models that allows for multidimensional unobserved heterogeneity. Our results rely on two main assumptions: treatment assignment must be a measurable function of threshold-crossing rules, and enough continuous instruments must be available. We illustrate our approach for several classes of models.
Keywords: Identi fication; selection; multivalued treatments; instruments; monotonicity; multidimensional unobserved heterogeneity (search for similar items in EconPapers)
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Journal Article: Identifying Effects of Multivalued Treatments (2018)
Working Paper: Identifying Effects of Multivalued Treatments (2018)
Working Paper: Identifying Effects of Multivalued Treatments (2015)
Working Paper: Identifying effects of multivalued treatments (2015)
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