This paper provides an elementary, non-technical, survey of auction theory, by introducing and describing some of the critical papers in the subject. (The most important of these are reproduced in a companion book, The Economic Theory of Auctions, Paul Klemperer (ed.), Edward Elgar (pub.), forthcoming.) We begin with the most fundamental concepts, and then introduce the basic analysis of optimal auctions, the revenue equivalence theorem, and marginal revenues. Subsequent sections address risk-aversion, affiliation, asymmetries, entry, collusion, multi-unit auctions, double auctions, royalties, incentive contracts, and other topics. Appendices contain technical details, some simple worked examples, and a bibliography for each section.

Economists have lately been called upon not only to analyze markets, but to design them. Market design involves a responsibility for detail, a need to deal with all of a market’s complications, not just its principle features. Designers therefore cannot work only with the simple conceptual models used for theoretical insights into the general working of markets. Instead, market design calls for an engineering approach. Drawing primarily on the design of the entry level labor market for American doctors (the National Resident Matching Program), and of the auctions of radio spectrum conducted by the Federal Communications Commission, this paper makes the case that experimental and computational economics are natural complements to game theory in the work of design. The paper also argues that some of the challenges facing both markets involve dealing with related kinds of complementarities, and that this suggests an agenda for future theoretical research.

This report describes simple mechanisms that allow autonomous software agents to engage in bargaining behaviors in market-based environments. Groups of agents with such mechanisms could be used in applications including market-based control, internet commerce, and economic modelling. After an introductory discussion of the rationale for this work, and a brief overview of key concepts from economics, work in market-based control is reviewed to highlight the need for bargaining agents. Following this, the early experimental economics work of Smith (1962) and the recent results of Gode and Sunder (1993) are described.

Abstract-- This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modified Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers, independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms. Index Terms – Wholesale electricity market, restructuring, repeated double auction, market power, efficiency, concentration, capacity, individual reinforcement learning, genetic algorithm social learning, agent-based computational economics. I.

This paper reports the results of a private-values auction experiment in which expected costs of deviating from the Nash equilibrium bidding function are asymmetric, with the implication that upward deviations will be more likely in one treatment than in the other. Overbidding is observed in both treatments, but is more prevalent in the treatment where the costs of overbidding are lower. We specify and estimate a noisy (quantal response) model of equilibrium behavior. Estimated noise and risk aversion parameters are highly significant and consistent across treatments. The resulting two-parameter model tracks both the average bids and the distribution of bids remarkably well. Alternative explanations of overbidding are also considered. The estimates of parameters from a nonlinear probability weighting function yield a formulation that is essentially equivalent to risk aversion in this context. A model in which players experience a "joy of winning " provides a reasonable fit of the data but does significantly worse than the risk aversion model. 1.

We experimentally investigate the sensitivity of bidders demanding multiple units of a homogeneous commodity to the demand reduction incentives inherent in uniform price auctions. There is substantial demand reduction in both sealed bid and ascending price clock auctions with feedback regarding rivals’ drop-out prices. Although both auctions have the same normal form representation, bidding is much closer to equilibrium in the ascending price auctions. We explore the behavioral process underlying these differences along with dynamic Vickrey auctions designed to eliminate the inefficiencies resulting from demand reduction in the uniform price auctions. Key words: multi-unit demand auctions, uniform price auction, dynamic Vickrey auction, demand reduction, experiment.

Auctions are a fundamental mechanism to automate negotiations in electronic commerce. We consider a class of multi-lateral negotiation situations, which requires negotiation on multiple attributes of a deal. These situations are typical for corporate procurement. Current auction implementations do not support these negotiations adequately. In the paper we propose multi-attribute auctions, an economic mechanism, which supports negotiation on multiple attributes of a deal. In this approach we combine decision analysis techniques and single -sided auction mechanisms to allocate tasks. We outline the theoretical questions associated with multiattribute auctions and describe an implementation of the proposed mechanism. In this context, we tackle several important issues concerning the design of electronic market places.

Sellers in eBay auctions have the opportunity to choose both a public minimum bid amount and a secret reserve price. We ask, empirically, whether the seller is made better or worse off by setting a secret reserve above a low minimum bid, versus the option of making the reserve public by using it as the minimum bid level. In a field experiment, we auction 50 matched pairs of Pokémon cards on eBay, half with secret reserves and half with equivalently high public minimum bids. We find that secret reserve prices make us worse off as sellers, by reducing the probability of the auction resulting in a sale, deterring serious bidders from entering the auction, and lowering the expected transaction price of the auction.

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Gode and Sunder's (1993) results from using "zero-intelligence" (zi) traders, that act randomly within a structured market, appear to imply that convergence to the theoretical equilibrium price in continuous double-auction markets is determined more by market structure than by the intelligence of the traders in that market. However, it is demonstrated here that the average transaction prices of zi traders can vary significantly from the theoretical equilibrium value when the market supply and demand are asymmetric, and that the degree of difference from equilibrium is predictable from a priori probabilistic analysis. In this sense, it is shown here that Gode and Sunder's results are artefacts of their experimental regime. Following this, `zero-intelligence-plus' (zip) traders are introduced: like zi traders, these simple agents make stochastic bids. Unlike zi traders, they employ an elementary form of machine learning. Groups of zip traders interacting in experimental markets...