Identifying Effects of Multivalued Treatments
Sokbae (Simon) Lee () and
Papers from arXiv.org
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.
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Journal Article: 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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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1805.00057
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