CRITICAL ISSUES IN THE PRACTICE OF MARKET DESIGN

I. INTRODUCTION For economic researchers hoping to influence the rules of real markets, 1994 was an auspicious year. It was a year of redesign for the National Resident Matching Program, whose rules were revised based on the recommendations of an academic researcher (Alvin Roth). And, it was the year of the first U.S. radio spectrum auctions, the rules for which were suggested in proposals by economic researchers (especially a proposal by Paul Milgrom and Robert Wilson and a related one by Preston McAfee). The exchanges between researchers and others who collaborated on those designs initiated a flood of activity among economic researchers contributing to the design of real markets. In matching, the initial leading applications were for matching students to schools and kidneys to patients (Abdulkadiroglu, Pathak, and Roth 2005; Abdulkadiroglu et al. 2005; Roth, Sonmez, and Unver 2005). In auctions, they included radio spectrum, electricity, and Internet advertising (Edelman, Ostrovsky, and Schwartz 2007; McMillan 1994; Milgrom 2000; Varian 2007; Wilson 2002). In the decade or so before 1994, the field of mechanism design was already established as a leading field of research in economic theory and game theory, but the focus on applications in the years that followed widened the range of questions being asked. As Roth (2002) has emphasized, market design is a kind of economic engineering and demands a comprehensive attention to implementation questions, including ones beyond the traditional scope of research in mechanism design theory. Solutions must be and have been invented, even when the analyses on which they are based are incomplete. In this paper, I revisit four fundamental issues that arise recurrently in the practice of auction market design, but which have not been satisfactorily resolved in mechanism design theory. The first issue concerns product definition. In the traditional economic and mechanism design models, the set of goods is treated as given to the modeler before any analysis begins. But that is unrealistic. In many real-world auction problems, the very first questions the designer must answer are about product definition. What are we selling (or buying)? What should be included in each lot? How is the commodity to be defined or the terms of the contract set? These questions can have deep implications for market rules and performance. A second issue concerns the messages transmitted in the mechanism. In the usual models of mechanism design, a type space is given in advance. In the simplest direct mechanisms, participants merely report their "value types," that is, they describe what they know about the values of the various possible outcomes. Although economic theorists have put growing emphasis on the very special assumptions required for this value-type approach to be adequate, they have devoted little attention to the reverse problem: the impracticality of reporting value information in problems of even modest size. With just 20 items for sale that can be bought in any combination, and even excluding the possibilities that a bidder cares about what others acquire or about the information they may have, a value-type is a list with more than a million entries! The impracticality of reporting so much information raises a fundamental question: if relevant information cannot be completely reported and described, how can one decide what messages should be used for a practical design? How do limits on reporting affect the performance that a mechanism can achieve? The third issue concerns the requirement to provide adequate incentives. The usual posture of mechanism design theory is that behavior will be consistent with some equilibrium concept, and this equilibrium concept defines a constraint on what can be achieved. But in practice, participants do not always play according to equilibrium, so this constraint is best regarded as an analytic device. Good market design can involve exploring the trade-offs between incentive compatibility of various kinds--including notions of approximate incentive compatibility--and other design goals. …