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Identifying Effects of Multivalued Treatments

Lee, Sobkae; Salanie, Bernard

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.

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More About This Work

Academic Units
Economics
Publisher
Department of Economics, Columbia University
Series
Department of Economics Discussion Papers, 1516-02
Published Here
December 2, 2015
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