OxTalks will soon move to the new Halo platform and will become 'Oxford Events.' There will be a need for an OxTalks freeze. This was previously planned for Friday 14th November – a new date will be shared as soon as it is available (full details will be available on the Staff Gateway).
In the meantime, the OxTalks site will remain active and events will continue to be published.
If staff have any questions about the Oxford Events launch, please contact halo@digital.ox.ac.uk
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
