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COMPLEMENTARITY AND IDENTIFICATION

  • Tate Twinam (a1)
Abstract

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.

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Corresponding author
*Address correspondence to Tate Twinam, 18115 Campus Way NE, Bothell, WA 98011, USA; e-mail: twinam@uw.edu.
Footnotes
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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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References
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Econometric Theory
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