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SUMMARY:Sharp and Robust Estimation of Partially Identified Discrete Respo
 nse Models - Tatiana Komarova (University of Cambridge)
DTSTART:20241108T140000Z
DTEND:20241108T150000Z
UID:TALK222253@talks.cam.ac.uk
CONTACT:Qingyuan Zhao
DESCRIPTION:Semiparametric discrete choice models are point identified wit
 h continuous covariates and may become partially identified with discrete 
 covariates. Classical estimators\, such as maximum score (Manski (1975))\,
  lose their desirable properties without point identification. They may no
 t be sharp\, converging to outer regions the identified set (Komarova (201
 3))\, and in many discrete designs\, weakly converge to random sets. They 
 lack robustness as their distribution limit changes discontinuously with m
 odel parameters. We propose a new class of estimators based on the quantil
 e of a random set\, which are both sharp and robust\, also applicable to s
 ingle-index and discrete panel data models.\n\n(joint work with S.Khan and
  D. Nekipelov)
LOCATION:Centre for Mathematical Sciences MR12\, CMS
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