DP10970 Identifying Effects of Multivalued Treatments

Author(s): Sokbae Lee, Bernard SalaniƩ
Publication Date: December 2015
Keyword(s): Discrete Choice, Identification, Monotonicity, Treatment evaluation
JEL(s): C14, C21
Programme Areas: Labour Economics, Development Economics
Link to this Page: www.cepr.org/active/publications/discussion_papers/dp.php?dpno=10970

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.