Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/130089
Authors: 
Lee, Sokbae
Salanie, Bernard
Year of Publication: 
2015
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP72/15
Abstract: 
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.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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