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DTSTART:20070311T020000
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DTSTAMP:20260331T092006
DTSTART;TZID=America/Detroit:20260410T100000
DTEND;TZID=America/Detroit:20260410T110000
SUMMARY:Workshop / Seminar:Statistics Department Seminar Series: Stefan Wager\, Associate Professor\, Department of Operations\, Information\, and Technology\, Department of Statistics (by courtesy)\, Stanford University
DESCRIPTION:We develop methods for estimating how infinitesimal policy changes affect long-term outcomes in dynamic systems. We show that dynamic marginal policy effects (MPEs) can be identified via tractable reduced-form expressions\, and can be estimated under a general sequential unconfoundedness assumption. We also propose a doubly robust estimator for dynamic MPEs. Our approach does not require observing full dynamic state information (as is typically assumed for off-policy evaluation in Markov decision processes)\, and does not incur an exponential curse of horizon (as is typical in non-Markovian off-policy evaluation). We demonstrate practicality and robustness of our approach in a number of simulations\, including one motivated by a dynamic pricing application where people use past prices to form a reference level for current prices. Joint work with I-han Lai.
UID:146702-21899507@events.umich.edu
URL:https://events.umich.edu/event/146702
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:seminar
LOCATION:West Hall - 340
CONTACT:
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