Person:

Maskin, Eric

A Nash equilibrium (called an “equilibrium point” by John Nash himself; see Nash 1950) of a game occurs when each player chooses a strategy from which unilateral deviations do not pay. The concept of Nash equilibrium is far and away Nash’s most important legacy to economics and the other behavioral sciences. This is because it remains the central solution concept—i.e., prediction of behavior—in applications of game theory to these fields. As I shall review below, Nash equilibrium has some important shortcomings, both theoretical and practical. I will argue, however, that these drawbacks are far less troublesome in problems of mechanism design than in many other applications of game theory.

I discuss recent work that characterizes what outcomes correspond to evolutionarily stable strategies in two-player symmetric repeated games when players have a positive probability of making a mistake.

Auctions, normally considered as devices facilitating trade, also provide a way to probe mechanisms governing one’s valuation of some good or action. One of the most intriguing phenomena in auction behavior is the winner’s curse — the strong tendency of participants to bid more than rational agent theory prescribes, often at a significant loss. The prevailing explanation suggests that humans have limited cognitive abilities that make estimating the correct bid difficult, if not impossible. Using a series of auction structures, we found that bidding approaches rational agent predictions when participants compete against a computer. However, the winner’s curse appears when participants compete against other humans, even when cognitive demands for the correct bidding strategy are removed. These results suggest the humans assign significant future value to victories over human but not over computer opponents even though such victories may incur immediate losses, and that this valuation anomaly is the origin of apparently irrational behavior.

We show that simple majority rule satisfies the Pareto property, anonymity, neutrality, and (generic) transitivity on a bigger class of preference domains than any other voting rule. If we replace neutrality in the above list of properties with independence of irrelevant alternatives, then the corresponding conclusion holds for unanimity rule (rule by consensus).

The theory of mechanism design can be thought of as the “engineering” side of economic theory. Much theoretical work, of course, focuses on existing economic institutions. The theorist wants to explain or forecast the economic or social outcomes that these institutions generate. But in mechanism design theory the direction of inquiry is reversed. We begin by identifying our desired outcome or social goal. We then ask whether or not an appropriate institution (mechanism) could be designed to attain that goal. If the answer is yes, then we want to know what form that mechanism might take. In this paper, I offer a brief introduction to the part of mechanism design called implementation theory, which, given a social goal, characterizes when we can design a mechanism whose predicted outcomes (i.e., the set of equilibrium outcomes) coincide with the desirable outcomes, according to that goal. I try to keep technicalities to a minimum, and usually confine them to footnotes.