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WELFARE ANALYSIS VIA MARGINAL TREATMENT EFFECTS

Published online by Cambridge University Press:  16 September 2024

Yuya Sasaki  and
Takuya Ura
Yuya Sasaki
Affiliation:
Vanderbilt University
Takuya Ura*
Affiliation:
University of California, Davis
*
Address correspondence to Takuya Ura, Department of Economics, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA; e-mail: takura@ucdavis.edu
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Abstract

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We consider a causal structure with endogeneity, i.e., unobserved confoundedness, where an instrumental variable is available. In this setting, we show that the mean social welfare function can be identified and represented via the marginal treatment effect as the operator kernel. This representation result can be applied to a variety of statistical decision rules for treatment choice, including plug-in rules, Bayes rules, and empirical welfare maximization rules. Focusing on the application of the empirical welfare maximization framework, we provide convergence rates of the worst-case average welfare loss (regret).

Type
ARTICLES
Information
Econometric Theory , First View , pp. 1 - 24
Copyright
© The Author(s), 2024. Published by Cambridge University Press

Footnotes

We thank Toru Kitagawa, Simon Lee, two anonymous referees, and the seminar participants at LMU Munich for their very useful comments. The usual disclaimers apply. Sasaki thanks Brian and Charlotte Grove Chair for research support.

References

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