Identifying Effects of Multivalued Treatments

60 Pages Posted: 9 Dec 2015

See all articles by Sokbae Lee

Sokbae Lee

Seoul National University

Bernard Salanie

Columbia University - Graduate School of Arts and Sciences - Department of Economics; CESifo (Center for Economic Studies and Ifo Institute)

Date Written: December 2015

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.

Keywords: Discrete Choice, Identification, Monotonicity, Treatment evaluation

JEL Classification: C14, C21

Suggested Citation

Lee, Sokbae and Salanie, Bernard, Identifying Effects of Multivalued Treatments (December 2015). CEPR Discussion Paper No. DP10970, Available at SSRN: https://ssrn.com/abstract=2701244

Sokbae Lee (Contact Author)

Seoul National University ( email )

Kwanak-gu
Seoul, 151-742
Korea, Republic of (South Korea)

Bernard Salanie

Columbia University - Graduate School of Arts and Sciences - Department of Economics ( email )

420 W. 118th Street
New York, NY 10027
United States

CESifo (Center for Economic Studies and Ifo Institute)

Poschinger Str. 5
Munich, DE-81679
Germany

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