Budget-Constrained Sequential Auctions with Incomplete Information

I study a budget-constrained, private-valuation, sealed-bid sequential auction with two incompletely-informed, risk-neutral bidders in which the valuations and income may be non-monotonic functions of a bidder's type. Multiple equilibrium symmetric bidding functions may exist that differ in allocation, efficiency and revenue. The sequence of sale affects the competition for a good and therefore also affects revenue and the prices of each good in a systematic way that depends on the relationship among the valuations and incomes of bidders. The sequence of sale may affect prices and revenue even when the number of bidders is large relative to the number of goods. If a particular good, say α, is allocated to a strong bidder independent of the sequence of sale, then auction revenue and the price of good α are higher when good α is sold first.sequential auctions, budget constraints, efficiency, revenue, price, sequence

Budget-Constrained Sequential Auctions with Incomplete Information

I study a budget-constrained, private-valuation, sealed-bid sequential auction with two incompletely-informed, risk-neutral bidders in which the valuations and income may be non-monotonic functions of a bidder\\'s type. Parameters permit the existence of multiple equilibrium symmetric bidding functions that differ in allocation, efficiency and revenue. The sequence of sale affects the competition for a good and therefore also affects revenue and the prices of each good in a systematic way that depends on the relationship among the valuations and incomes of bidders. The sequence of sale may affect prices and revenue even when the number of bidders is large relative to the number of goods. If a particular good, say α, is allocated to a strong bidder independent of the sequence of sale, then auction revenue and the price of good α is higher when good α is sold first.sequential auctions, budget constraints, efficiency, revenue, price, sequence.

Budget Constrained Auctions with Heterogeneous Items

In this paper, we present the first approximation algorithms for the problem of designing revenue optimal Bayesian incentive compatible auctions when there are multiple (heterogeneous) items and when bidders can have arbitrary demand and budget constraints. Our mechanisms are surprisingly simple: We show that a sequential all-pay mechanism is a 4 approximation to the revenue of the optimal ex-interim truthful mechanism with discrete correlated type space for each bidder. We also show that a sequential posted price mechanism is a O(1) approximation to the revenue of the optimal ex-post truthful mechanism when the type space of each bidder is a product distribution that satisfies the standard hazard rate condition. We further show a logarithmic approximation when the hazard rate condition is removed, and complete the picture by showing that achieving a sub-logarithmic approximation, even for regular distributions and one bidder, requires pricing bundles of items. Our results are based on formulating novel LP relaxations for these problems, and developing generic rounding schemes from first principles. We believe this approach will be useful in other Bayesian mechanism design contexts.Comment: Final version accepted to STOC '10. Incorporates significant reviewer comment

Learning optimization models in the presence of unknown relations

In a sequential auction with multiple bidding agents, it is highly challenging to determine the ordering of the items to sell in order to maximize the revenue due to the fact that the autonomy and private information of the agents heavily influence the outcome of the auction. The main contribution of this paper is two-fold. First, we demonstrate how to apply machine learning techniques to solve the optimal ordering problem in sequential auctions. We learn regression models from historical auctions, which are subsequently used to predict the expected value of orderings for new auctions. Given the learned models, we propose two types of optimization methods: a black-box best-first search approach, and a novel white-box approach that maps learned models to integer linear programs (ILP) which can then be solved by any ILP-solver. Although the studied auction design problem is hard, our proposed optimization methods obtain good orderings with high revenues. Our second main contribution is the insight that the internal structure of regression models can be efficiently evaluated inside an ILP solver for optimization purposes. To this end, we provide efficient encodings of regression trees and linear regression models as ILP constraints. This new way of using learned models for optimization is promising. As the experimental results show, it significantly outperforms the black-box best-first search in nearly all settings.Comment: 37 pages. Working pape

An Ascending Multi-Item Auction with Financially Constrained Bidders

A number of heterogeneous items are to be sold to a group of potential bidders. Every bidder knows his own values over the items and his own budget privately. Due to budget constraint, bidders may not be able to pay up to their values. In such a market, a Walrasian equilibrium typically fails to exist and furthermore no existing allocation mechanism can tackle this case. We propose the notion of an `equilibrium under allotment' to such markets and develop an ascending auction mechanism that always finds such an equilibrium assignment and corresponding price system in finitely many rounds. The auction can be viewed as an appropriate and proper generalization of the ascending auction of Demange, Gale and Sotomayor from settings without financial constraints to settings with financial constraints. We examine various properties of the auction and its outcome.Ascending auction, Financial constraint, Equilibrium under allotment.

Auction with aftermarket for budget constrained bidders

The paper compares different auction formats for sale of a single patented innovation for budget constrained bidders. This unit decreases the marginal cost of production in the aftermarket for its owner by an amount which depends on the money invested on the development of this technology. As the bidders have a fixed budget that must be used to pay the final auction price and also to develop the new technology, the winner has incentives to pay a low amount for his unit to increase the amount available to invest in cost reduction. Conversely the loser has incentives to induce induce a higher price to be paid by the winner in order to increase aftermarket profits. This conflict of interest generates the willingness to pay (WTP) for the patent through an endogenous process, which may end up by stablishing a higher WTP for the lowest financed firm. Given this background, the case in which the players have different initial budgets may generate multiple equilibria for all studied auction mechanisms. These equilibria produce di¤erent consumer surplus and, thus, a central government with an unti-trust behavior is able to choose the auction that generates the re�ned equilibrium leading to the highest consumer surplus.Market design; auction; aftermarket; budget constraints; investment

Putting auction theory to work : the simultaneous ascending auction

The"simultaneous ascending auction"was first introduced in 1994 to sell licenses to use bands of radio spectrum in the United States. Much of the attention devoted to the auction came from its role in reducing federal regulation of the radio spectrum and allowing market values, rather than administrative fiat, to determine who would use the spectrum resource. Several parts of economic theory proved helpful in designing the rules for simultaneous ascending auction and in thinking about how the design might be improved and adapted for new applications. After briefly reviewing the major rules of the auction in section 2, the author turns in section 3 to an analysis based on tatonnement theory, which regards the auction as a mechanism for discovering an efficient allocation and its supporting prices. The analysis reveals a fundamental difference between situations in which the licenses are mutual substitutes and others in which the same licenses are sometimes substitutes and sometimes complements. Section 4 is a selective account of some applications of game theory to evaluating the simultaneous ascending auction design for spectrum sales. Results like those reported in section 3 have led to renewed interest in auctions in which bids for license packages are permitted. In section 5, the author uses game theory to analyze the biases in a leading proposal for dynamic combinatorial bidding. Section 6 briefly answers two additional questions that economists often ask about auction design: If trading of licenses after the auction is allowed, why does the auction form matter at all for promoting efficient license assignments? Holding fixed the quantity of licenses to be sold, how sharp is the conflict between the objectives of assigning licenses efficiently and obtaining maximum revenue? Section 7 concludes.Economic Theory&Research,International Terrorism&Counterterrorism,Markets and Market Access,Environmental Economics&Policies,Labor Policies,Markets and Market Access,Access to Markets,Economic Theory&Research,Environmental Economics&Policies,International Terrorism&Counterterrorism

An Efficient Multi-Item Dynamic Auction with Budget Constrained Bidders

An auctioneer wishes to sell several heterogeneous indivisible items to a group of potential bidders. Each bidder has valuations over the items but faces a budget constraint and may therefore not be able to pay up to his valuations. In such markets, a competitive equilibrium typically fails to exist. We develop a dynamic auction and prove that the auction always finds a core allocation in finitely many rounds. The core allocation consists of an assignment of the items and its associated supporting price vector.Dynamic auction;budget constraint;core