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Applied Micro Workshop – Ran Spiegler, “The Variable Selection Curse”

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Kfir Eliaz and Ran Spiegler: “The Variable Selection Curse” We study a model in which a “classical statistician” takes an action on behalf of an agent, based on a random sample involving other agents. The statistician estimates a predictive model, and the action that he takes is the model’s estimate given the agent’s disclosed personal characteristics. The estimation procedure involves variable selection (in the spirit of methods like LASSO). We ask the following question: Is truth-telling an optimal disclosure strategy for the agent, given the statistician’s procedure? In particular, could the agent be better off by always reporting “default” values for all personal characteristics? We discuss the possible implications of our theoretical exercise for the increasing reliance on “machine learning” methods that involve explicit variable selection in various real-life settings, such as online content provision.

Event details
  • Presentation
When Oct 17, 2017
from 17:15 to 18:00
Where briq, Seminar Room 9/1.1, Schaumburg-Lippe-Straße 9
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