We explore the impact of private information in sealed bid first price auctions. For a given symmetric and arbitrarily correlated prior distribution over values, we characterize the lowest winning bid distribution that can arise across all information structures and equilibria. The information and equilibrium attaining this minimum leave bidders uncertain whether they will win or lose and indifferent between their equilibrium bids and all higher bids. Our results provide lower bounds for bids and revenue with asymmetric distributions over values. We report further analytic and computational characterizations of revenue and bidder surplus including upper bounds on revenue. Our work has implications for the identification of value distributions from winning bid data and for the informationally robust comparison of alternative bidding mechanisms.

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BFI Working Paper Feb 1, 2016

A “Pencil Sharpening” Algorithm for Two Player Stochastic Games with Perfect Monitoring

Dilip J. Abreau, Benjamin Brooks, Yuliy Sannikov
Topics:  Fiscal Studies