An Equilibrium Model of the First-Price Auction with Strategic Uncertainty: Theory and Empirics
In many first-price auctions, bidders face considerable strategic uncertainty: They cannot perfectly anticipate the other bidders' bidding behavior. We propose a model in which bidders do not know the entire distribution of opponent bids but only the expected (winning) bid and lower and upper bounds on the opponent bids. We characterize the optimal bidding strategies and prove the existence of equilibrium beliefs. Finally, we apply the model to estimate the cost distribution in highway procurement auctions and find good performance out-of-sample.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Learning to Coordinate Bidders in Non-Truthful Auctions
In non-truthful auctions such as first-price and all-pay auctions, the independent strategic behaviors of bidders, with the corresponding Bayes-Nash equilibrium notion, are notoriously difficult to characterize and can c…
From No-Regret to Strategically Robust Learning in Repeated Auctions
In Bayesian single-item auctions, a monotone bidding strategy--one that prescribes a higher bid for a higher value type--can be equivalently represented as a partition of the quantile space into consecutive intervals cor…
Reserve Pricing in Repeated Second-Price Auctions with Strategic Bidders
We study revenue optimization learning algorithms for repeated second-price auctions with reserve where a seller interacts with multiple strategic bidders each of which holds a fixed private valuation for a good and seek…
Scoring Auctions with Coarse Beliefs
This paper studies a simplicity notion in a mechanism design setting in which agents do not necessarily share a common prior. I develop a model in which agents participate in a prior-free game of (coarse) information acq…
Non-parametric Revenue Optimization for Generalized Second Price Auctions
We present an extensive analysis of the key problem of learning optimal reserve prices for generalized second price auctions. We describe two algorithms for this task: one based on density estimation, and a novel algorit…
Density Estimation