Discussion paper

DP10970 Identifying Effects of Multivalued Treatments

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.


Salanié, B (2015), “DP10970 Identifying Effects of Multivalued Treatments”, CEPR Press Discussion Paper No. 10970. https://cepr.org/publications/dp10970