Identifying Effects of Multivalued Treatments

Salanié, Bernard
Authors registered in the RePEc Author Service: Bernard Salanié and Sokbae (Simon) Lee

No 10970, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: 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)
Date: 2015-12
New Economics Papers: this item is included in nep-dcm and nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Related works:
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)
Working Paper: Identifying effects of multivalued treatments (2015)
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