Identifying Effects of Multivalued Treatments
Sokbae (Simon) Lee () and
Bernard Salanié ()
No 10970, CEPR Discussion Papers from C.E.P.R. Discussion Papers
Multivalued treatment models have only been studied so far under restrictive assumptions: ordered choice, or more recently unordered monotonicity. We show how marginal treatment effects can be identified in a more general class of models. 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. On the other hand, we do not require any kind of monotonicity condition. We illustrate our approach on several commonly used models; and we also discuss the identification power of discrete instruments.
Keywords: Discrete Choice; Identification; Monotonicity; Treatment evaluation (search for similar items in EconPapers)
JEL-codes: C14 C21 (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 (2018)
Working Paper: Identifying effects of multivalued treatments (2015)
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