Open AccessCountering the winner's curse: Optimal auction design in a common value model
Author(s) -
Bergemann Dirk,
Brooks Benjamin,
Morris Stephen
Publication year - 2020
Publication title -
theoretical economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.404
H-Index - 32
eISSN - 1555-7561
pISSN - 1933-6837
DOI - 10.3982/te3797
Subject(s) - winner's curse , common value auction , revenue , english auction , vickrey auction , curse , revenue equivalence , value (mathematics) , object (grammar) , microeconomics , vickrey–clarke–groves auction , economics , generalized second price auction , auction theory , mechanism design , skew , mathematical economics , computer science , finance , telecommunications , machine learning , artificial intelligence , sociology , anthropology
We characterize revenue maximizing mechanisms in a common value environment where the value of the object is equal to the highest of the bidders' independent signals. If the revenue maximizing solution is to sell the object with probability 1, then an optimal mechanism is simply a posted price, namely, the highest price such that every type of every bidder is willing to buy the object. If the object is optimally sold with probability less than 1, then optimal mechanisms skew the allocation toward bidders with lower signals. The resulting allocation induces a “winner's blessing,” whereby the expected value conditional on winning is higher than the unconditional expectation. By contrast, standard auctions that allocate to the bidder with the highest signal (e.g., the first‐price, second‐price, or English auctions) deliver lower revenue because of the winner's curse generated by the allocation. Our qualitative results extend to more general common value environments with a strong winner's curse.