Identifying Effects of Multivalued Treatments

• 成果类型: Article
• 署名作者: Lee, Sokbae; Salanie, Bernard
• 署名单位: Columbia University; University of London; London School Economics & Political Science
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA14269
• 发表日期: 2018
• 页码: 1939-1963
• 关键词: instrumental variables; nonseparable models; propensity score; identification; EQUATIONS

摘要

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.