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STICERD Econometrics Seminar Series

Optimal Dynamic Treatment Regimes and Partial Welfare Ordering

Sukjin Han (University of Bristol)

Thursday 25 November 2021 14:00 - 15:30

Many of our seminars and public events this year will continue as in person or as hybrid (online and in person) events. Please check our website listings and Twitter feed @STICERD_LSE for updates.

Unless otherwise specified, in-person seminars are open to the public.

Those unable to join the seminars in-person are welcome to participate via zoom if the event is hybrid.

About this event

Dynamic treatment regimes are treatment allocations tailored to heterogeneous individuals. The optimal dynamic treatment regime is a regime that maximizes counterfactual welfare. We introduce a framework in which we can partially learn the optimal dynamic regime from observational data, relaxing the sequential randomization assumption commonly employed in the literature but instead using (binary) instrumental variables. We propose the notion of sharp partial ordering of counterfactual welfares with respect to dynamic regimes and establish mapping from data to partial ordering via a set of linear programs. We then characterize the identified set of the optimal regime as the set of maximal elements associated with the partial ordering. We relate the notion of partial ordering with a more conventional notion of partial identification using topological sorts. Practically, topological sorts can be served as a policy benchmark for a policymaker. We apply our method to understand returns to schooling and post-school training as a sequence of treatments by combining data from multiple sources. The framework of this paper can be used beyond the current context, e.g., in establishing rankings of multiple treatments or policies across different counterfactual scenarios.

STICERD Econometrics seminars are held on Thursdays in term time at 14.00-15.30, in SAL 3.05, unless specified otherwise.

Seminar organisers: Professor Tai Otsu and Dr. Vassilis Hajivassiliou.

For further information please contact Sadia Ali:

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