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Identifying effects of multivalued treatments

Authors: Sokbae (Simon) Lee and Bernard Salanie
Date: 12 June 2018
Type: cemmap Working Paper, CWP34/18

Abstract

Multivalued treatment models have typically been studied under restrictive assumptions: ordered choice, and more recently unordered monotonicity. We show how treatment effects can be identi fied 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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Sokbae (Simon) Lee and Bernard Salanie December 2015, Identifying effects of multivalued treatments, cemmap Working Paper, CWP72/15, Institute for Fiscal Studies

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