Oxford Events, the new replacement for OxTalks, will launch on 16th March. The two-week OxTalks freeze period starts on Monday 2nd March. During this time, there will be no facility to publish or edit events. The existing OxTalks site will remain available to view during this period. Once Oxford Events launches, you will need a Halo login to submit events. Full details are available on the Staff Gateway.
Do more competitive auctions better aggregate private information? Suppose n identical objects are offered for sale to k symmetric bidders with interdependent values. Do the n winning bids reveal more information about the state of demand for these objects when the number of bidders k rises? We find that competition decreases information if bidders’ private signals have a log-submodular reverse hazard rate function – overturning received wisdom. When private signals derive from a location family, and only one object is for sale (n=1), competition harms information aggregation if and only if the signal’s noise component follows a distribution which is less convex than Gumbel’s extreme value distribution. Drawing on extreme value theory, we quantify the amount of information in the perfectly competitive limit.
Please sign up for meetings here: docs.google.com/spreadsheets/d/1G0KdCfEkG4LYBuDSCLxyGRSEULv3_smLEEQMofG4X5U/edit#gid=0
