Auctions: Theory and Practice

Governments use them to sell everything from oilfields to pollution permits, and to privatize companies; consumers rely on them to buy baseball tickets and hotel rooms, and economic theorists employ them to explain booms and busts. Auctions make up many of the world's most important markets; and this book describes how auction theory has also become an invaluable tool for understanding economics. Auctions: Theory and Practice provides a non-technical introduction to auction theory, and emphasises its practical application. Although there are many extremely successful auction markets, there have also been some notable fiascos, and Klemperer provides many examples. He discusses the successes and failures of the one-hundred-billion dollar "third-generation" mobile-phone license auctions; he, jointly with Ken Binmore, designed the first of these. Klemperer also demonstrates the surprising power of auction theory to explain seemingly unconnected issues such as the intensity of different forms of industrial competition, the costs of litigation, and even stock trading 'frenzies' and financial crashes. Engagingly written, the book makes the subject exciting not only to economics students but to anyone interested in auctions and their role in economics.markets, industrial competition, litigation, stock trading, financial crashes

Bidding Behavior in Multi-Unit Auctions - An Experimental Investigation

We present laboratory experiments of five different multi-unit auction mechanisms. Two units of a homogeneous object were auctioned off among two bidders with flat demand for two units. We test whether expected demand reduction occurs in open and sealed-bid uniform-price auctions. Revenue equivalence is tested for these auctions as well as for the Ausubel, the Vickrey and the discriminatory sealed-bid auction. Furthermore, we compare the five mechanisms with respect to the efficient allocation of the units.Multi-Unit Auctions, Demand Reduction, Experimental Economics

Ascending Auctions

A key question of auction design is whether to use an ascending- bid or a sealed-bid format. The critical distinction between formats is that an ascending auction provides the bidders with information through the process of bidding. This information is a two-edged sword. It may stimulate competition by creating a reliable process of price discovery, by reducing the winner's curse, and by allowing efficient aggregations of items. Alternatively, the information may be used by bidders to establish and enforce collusive outcomes. Ex ante asymmetries and weak competition favor a sealed-bid design. In other cases, an ascending auction is likely to perform better in efficiency and revenue terms. Moreover, information in an ascending auction can be tailored to limit collusion.Auctions; Multiple-Item Auctions, Spectrum Auctions

Using and Abusing Economic Theory

Economic Theory is often abused in practical policy-making. There is frequently excessive focus on sophisticated theory at the expense of elementary theory; too much economic knowledge can sometimes be a dangerous thing. Too little attention is paid to the wider economic context, and to the dangers posed by political pressures. Superficially trivial distinctions between policy proposals may be economically significant, while economically irrelevant distinctions may be politically important. I illustrate with some disastrous government auctions, but also show the value of economic theory.

Applying revenue management to agent-based transportation planning

We consider a multi-company, less-than-truckload, dynamic VRP based on the concept of multi-agent systems. We focus on the intelligence of one vehicle agent and especially on its bidding strategy. We address the problem how to price loads that are offered in real-time such that available capacity is used in the most profitable way taking into account possible future revenues. We develop methods to price loads dynamically based on revenue management concepts.\ud We consider a one leg problem, i.e., a vehicle travels from i to j and can wait at most τ time units in which it can get additional loads from i to j. We develop a DP to price loads given a certain amount of remaining capacity and an expected number of auctions in the time-to-go. Because a DP might be impractical if parameters change frequently and bids has to be determined in real-time, we derived two approximations to speed up calculations. The performance of these approximations are compared with the performance of the DP. Besides we introduce a new measure to calculate the average vehicle utilisation in consolidated shipments. This measure can be calculated based on a limited amount of data and gives an indication of the efficiency of schedules and the performance of vehicles

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

Collusive Bidding: Lessons from the FCC Spectrum Auctions

The Federal Communications Commission (FCC) spectrum auctions use a simultaneous ascending auction design. Bidders bid on numerous communication licenses simultaneously, with bidding remaining open on all licenses until no bidder is willing to bid higher on any license. With full revelation of bidding information, simultaneous open bidding allows bidders to send messages to their rivals, telling them on which licenses to bid and which to avoid. These strategies can help bidders coordinate a division of the licenses, and enforce the proposed division by directed punishments. We examine solutions to mitigate collusive bidding in the spectrum auctions, and then apply these ideas to the design of daily electricity auctions.Auctions, Collusion; Multiple Object Auctions; Spectrum Auctions

Bidding Markets

The existence of a ‘bidding market’ is commonly cited as a reason to tolerate the creation or maintenance of highly concentrated markets. We discuss three erroneous arguments to that effect: the ‘consultants’ fallacy’ that ‘market power is impossible’, the ‘academics’ fallacy’ that (often) ‘market power does not matter’, and the ‘regulators’ fallacy’ that ‘intervention against pernicious market power is unnecessary’, in markets characterized by auctions or bidding processes. Furthermore we argue that the term ‘bidding market’ as it is widely used in antitrust is unhelpful or misleading. Auctions and bidding processes do have some special features—including their price formation processes, common-values behaviour, and bid-taker power—but the significance of these features has been overemphasized, and they often imply a need for stricter rather than more lenient competition policy.Bidding Markets, Auctions, Antitrust, Competition Policy, Bidding, Market Power, Private Values, Common Values, Anti-trust

Competition in Electricity Spot Markets: Economic Theory and International Experience

auctions, electricity markets