AbstractMany empirical questions concern target parameters selected through optimization. For example, researchers may be interested in the effectiveness of the best policy found in a randomized trial, or the best-performing investment strategy based on historical data. Such settings give rise to a winner’s curse, where conventional estimates are biased and conventional confidence intervals are unreliable. This paper develops optimal confidence intervals and median-unbiased estimators that are valid conditional on the target selected and so overcome this winner’s curse. If one requires validity only on average over targets that might have been selected, we develop hybrid procedures that combine conditional and projection confidence intervals to offer further performance gains relative to existing alternatives.
Where: CGIS Knafel Building, Room K354
(See
this link for directions).
When: Wednesday, November 10 at 12:10 - 1:30 pm.
(Bagged lunches available for pick-up at CGIS K354
11:30 - 11:45 am, for the participants who responded to our previous survey. The CGIS cafe on the first floor has been designated as an eating area, and participants may also use outdoor spaces for lunch. Please be present at K354 by 12:10 pm for the presentations.)
Zoom link:
https://harvard.zoom.us/j/97004196610?pwd=eGFydkF5RDRjUlk5RVcyTjV6OStUQT09(For the participants who cannot join the session physically.)
Schedule of the workshop:
https://projects.iq.harvard.edu/applied.stats.workshop-gov3009Looking forward to seeing you all on Wednesday!
Best,
Sooahn