scholarly journals Optimal Auction Design in a Common Value Model

2016 ◽  
Author(s):  
Dirk Bergemann ◽  
Benjamin A. Brooks ◽  
Stephen Morris
Keyword(s):  
Auction Design ◽  
Common Value ◽  
Optimal Auction ◽  
Value Model

scholarly journals Countering the Winner’s Curse: Optimal Auction Design in a Common Value Model

2018 ◽  
Author(s):  
Dirk Bergemann ◽  
Benjamin A. Brooks ◽  
Stephen Edward Morris
Keyword(s):  
Winner's Curse ◽  
Auction Design ◽  
Winner’S Curse ◽  
Common Value ◽  
Optimal Auction ◽  
Value Model

scholarly journals Selling to Intermediaries: Optimal Auction Design in a Common Value Model

2017 ◽  
Author(s):  
Dirk Bergemann ◽  
Benjamin A. Brooks ◽  
Stephen Edward Morris
Keyword(s):  
Auction Design ◽  
Common Value ◽  
Optimal Auction ◽  
Value Model

scholarly journals Countering the Winner’s Curse: Optimal Auction Design in a Common Value Model

2019 ◽  
Author(s):  
Dirk Bergemann ◽  
Benjamin Brooks ◽  
Stephen Edward Morris
Keyword(s):  
Winner's Curse ◽  
Auction Design ◽  
Winner’S Curse ◽  
Common Value ◽  
Optimal Auction ◽  
Value Model

scholarly journals Countering the winner's curse: Optimal auction design in a common value model

2020 ◽  
Vol 15 (4) ◽  
pp. 1399-1434
Author(s):  
Dirk Bergemann ◽  
Benjamin Brooks ◽  
Stephen Morris
Keyword(s):  
Expected Value ◽  
Winner's Curse ◽  
English Auctions ◽  
Auction Design ◽  
Winner’S Curse ◽  
Common Value ◽  
Optimal Mechanism ◽  
Optimal Auction ◽  
Value Model ◽  
Posted Price

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.

scholarly journals Optimal Auction Design With Common Values: An Informationally Robust Approach

Econometrica ◽  
2021 ◽  
Vol 89 (3) ◽  
pp. 1313-1360
Author(s):  
Benjamin Brooks ◽  
Songzi Du
Keyword(s):  
Mechanism Design ◽  
Information Structure ◽  
Single Unit ◽  
Information Design ◽  
Design Problems ◽  
Auction Design ◽  
One Dimensional ◽  
Common Value ◽  
Optimal Auction ◽  
Joint Mechanism

A profit‐maximizing seller has a single unit of a good to sell. The bidders have a pure common value that is drawn from a distribution that is commonly known. The seller does not know the bidders' beliefs about the value and thinks that beliefs are designed adversarially by Nature to minimize profit. We construct a strong maxmin solution to this joint mechanism design and information design problem, consisting of a mechanism, an information structure, and an equilibrium, such that neither the seller nor Nature can move profit in their respective preferred directions, even if the deviator can select the new equilibrium. The mechanism and information structure solve a family of maxmin mechanism design and minmax information design problems, regardless of how an equilibrium is selected. The maxmin mechanism takes the form of a proportional auction: each bidder submits a one‐dimensional bid, the aggregate allocation and aggregate payment depend on the aggregate bid, and individual allocations and payments are proportional to bids. We report a number of additional properties of the maxmin mechanisms, including what happens as the number of bidders grows large and robustness with respect to the prior over the value.

Optimal Auction Design with Deferred Inspection and Reward

2020 ◽  
Author(s):  
Saeed Alaei ◽  
Alexandre Belloni ◽  
Ali Makhdoumi ◽  
Azarakhsh Malekian
Keyword(s):  
Auction Design ◽  
Optimal Auction

scholarly journals Informationally Robust Optimal Auction Design

2016 ◽  
Author(s):  
Dirk Bergemann ◽  
Benjamin A. Brooks ◽  
Stephen Morris
Keyword(s):  
Auction Design ◽  
Optimal Auction

Analyzing the Dual Channels for Online Retailer

2011 ◽  
Vol 48-49 ◽  
pp. 232-235
Author(s):  
Sheng Li Chen
Keyword(s):  
Decision Model ◽  
Design Principle ◽  
Optimal Decision ◽  
Threshold Policy ◽  
Auction Design ◽  
Decision Variables ◽  
Optimal Auction ◽  
Dual Channels ◽  
High Valuation ◽  
Dual Mechanism

By constructing the exponential delay cost function, we formulate the consumer decision model based on the threshold strategies in dual-mechanism, and prove that there exists a unique symmetric Nash equilibrium in which the high-valuation consumers use a threshold policy to choose between the two selling channels. On the basis of the consumer’s threshold strategies, taking the auction length, the auctioned quantity in each period, and the posted price as the decision variables, we develop the seller’ optimal decision model in dual-mechanism, and show the optimal auction design principle and strategy by numerical analysis.

Optimal Auction Design With Common Values: An Informationally-Robust Approach

2018 ◽  
Author(s):  
Benjamin A. Brooks ◽  
Songzi Du
Keyword(s):  
Auction Design ◽  
Robust Approach ◽  
Common Values ◽  
Optimal Auction
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