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The Department of Economics and Finance at the Institute for Advanced Studies cordially invites you to the following Econometrics Research Seminar
Thursday, November 12, 2015
Attention – New Address
Institute for Advanced Studies
Josefstädter Straße 39, 1080 Vienna
Seminar Room 101, 1st floor
9:00 am (Please note that the seminar will start at 9 am sharp!)
Toru Kitagawa
University College London
Who should be treated? Empirical welfare maximization methods for treatment choice
Abstract: One of the main objectives of empirical analysis of experiments and quasi-experiments is to inform policy decisions that determine the allocation of treatments to individuals with different observable covariates. We
propose the Empirical Welfare Maximization (EWM) method, which estimates a treatment assignment policy by maximizing the sample analog of average social welfare over a class of candidate treatment policies. The EWM approach is attractive in terms of both statistical
performance and practical implementation in realistic settings of policy design. Common features of these settings include: (i) feasible treatment assignment rules are constrained exogenously for ethical, legislative, or political reasons, (ii) a policy maker
wants a simple treatment assignment rule based on one or more eligibility scores in order to reduce the dimensionality of individual observable characteristics, and/or (iii) the proportion of individuals who can receive the treatment is a priori limited due
to a budget or a capacity constraint. We show that when the propensity score is known, the average social welfare attained by EWM rules converges at least at n^(-1/2) rate to the maximum obtainable welfare uniformly over a minimally constrained class of data
distributions, and this uniform convergence rate is minimax optimal. In comparison with this benchmark rate, we examine how the uniform convergence rate of the average welfare improves or deteriorates depending on the richness of the class of candidate decision
rules, the distribution of conditional treatment effects, and the lack of knowledge of the propensity score. We provide an asymptotically valid inference procedure for the population welfare gain obtained by exercising the EWM rule. We offer easily implementable
algorithms for computing the EWM rule and an application using experimental data from the National JTPA Study.
Paper jointly with Aleksey Teteno
We are looking forward to seeing you!
Institute for Advanced Studies
Department of Economics and Finance
Josefstädter Straße 39, 1080 Vienna, Austria
Tel.: +43 1 599 91 145
e-Mail:
economics@ihs.ac.at
http://economics.ihs.ac.at
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