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COMPLEMENTARITY AND IDENTIFICATION

Published online by Cambridge University Press:  20 September 2016

Tate Twinam
Tate Twinam*
Affiliation:
University of Washington
*
*Address correspondence to Tate Twinam, 18115 Campus Way NE, Bothell, WA 98011, USA; e-mail: twinam@uw.edu.
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Abstract

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This paper examines the identification power of assumptions that formalize the notion of complementarity in the context of a nonparametric bounds analysis of treatment response. I extend the literature on partial identification via shape restrictions by exploiting cross-dimensional restrictions on treatment response when treatments are multidimensional; the assumption of supermodularity can strengthen bounds on average treatment effects in studies of policy complementarity. This restriction can be combined with a statistical independence assumption to derive improved bounds on treatment effect distributions, aiding in the evaluation of complex randomized controlled trials. Complementarities arising from treatment effect heterogeneity can be incorporated through supermodular instrumental variables to strengthen identification in studies with one or multiple treatments. An application examining the long-run impact of zoning on the evolution of urban spatial structure illustrates the value of the proposed identification methods.

Information

Type
ARTICLES
Information
Econometric Theory , Volume 33 , Issue 5 , October 2017 , pp. 1154 - 1185
Copyright
Copyright © Cambridge University Press 2016 

Footnotes

I am indebted to Arie Beresteanu for his support and feedback on multiple drafts. Additionally, constructive comments from two anonymous referees and the editors Victor Chernozhukov and Peter Phillips substantially improved the quality of the paper.

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