Identifying effects of multivalued treatments. (English) Zbl 1416.62268
Summary: Multivalued treatment models have typically been studied under restrictive assumptions: ordered choice, and more recently, unordered monotonicity. We show how treatment effects can be identified in a more general class of models that allows for multidimensional unobserved heterogeneity. 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. We illustrate our approach for several classes of models.
MSC:
| 62G30 | Order statistics; empirical distribution functions |
| 62P20 | Applications of statistics to economics |
Keywords:
identification; selection; multivalued treatments; instruments; monotonicity; multidimensional unobserved heterogeneity; ordered choiceReferences:
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