Behavioral and Quantitative Game Theory on Conference on Future Directions 

About: Behavioral and Quantitative Game Theory on Conference on Future Directions is an academic conference. The conference publishes majorly in the area(s): Repeated game & Nash equilibrium. Over the lifetime, 72 publications have been published by the conference receiving 1389 citations.

The combinatorial assignment problem: approximate competitive equilibrium from equal incomes

Abstract: Impossibility theorems suggest that the only efficient and strategyproof mechanisms for the problem of combinatorial assignment - e.g., assigning schedules of courses to students - are dictatorships. Dictatorships are mostly rejected as unfair: for any two agents, one chooses all their objects before the other chooses any. Any solution will involve compromise amongst efficiency, incentive and fairness considerations.This paper proposes a solution to the combinatorial assignment problem. It is developed in four steps. First, I propose two new criteria of outcome fairness, the maximin share guarantee and envy bounded by a single good, which weaken well-known criteria to accommodate indivisibilities; the criteria formalize why dictatorships are unfair. Second, I prove existence of an approximation to Competitive Equilibrium from Equal Incomes in which (i) incomes are unequal but arbitrarily close together; (ii) the market clears with error, which approaches zero in the limit and is small for realistic problems. Third, I show that this Approximate CEEI satisfies the fairness criteria. Last, I define a mechanism based on Approximate CEEI that is strategyproof for the zero-measure agents economists traditionally regard as price takers. The proposed mechanism is calibrated on real data and is compared to alternatives from theory and practice: all other known mechanisms are either manipulable by zero-measure agents or unfair ex-post, and most are both manipulable and unfair.

Multi-parameter mechanism design and sequential posted pricing

Abstract: We consider the classical mathematical economics problem of Bayesian optimal mechanism design where a principal aims to optimize expected revenue when allocating resources to self-interested agents with preferences drawn from a known distribution. In single-parameter settings (i.e., where each agent's preference is given by a single private value for being served and zero for not being served) this problem is solved. Unfortunately, these single parameter optimal mechanisms are impractical and rarely employed, and furthermore the underlying economic theory fails to generalize to the important, relevant, and unsolved multi-dimensional setting (i.e., where each agent's preference is given by multiple values for each of the multiple services available). In contrast to the theory of optimal mechanisms we develop a theory of sequential posted price mechanisms, where agents in sequence are offered take-it-or-leave-it prices. We prove that these mechanisms are approximately optimal in single-dimensional settings. These posted-price mechanisms avoid many of the properties of optimal mechanisms that make the latter impractical. Furthermore, these mechanisms generalize naturally to multidimensional settings where they give the first known approximations to the elusive optimal multi-dimensional mechanism design problem.

Identification in matching games

Abstract: I study a many-to-many, two-sided, transferable-utility matching game. Consider data on matches or relationships between agents but not on the choice set of each agent. I investigate what economic parameters can be learned from data on equilibrium matches and agent characteristics. Features of a production function, which gives the surplus from a match, are nonparametrically identified. In particular, the ratios of complementarities from multiple pairs of inputs are identified. Also, the ordering of production levels is identified.

Favoritism in asymmetric contests: head starts and handicaps

Abstract: I examine a contest with identity-dependent rules in which contestants are privately informed and ex ante heterogenous. A contestant may suffer from a handicap or benefit from a head start. The former reduces the contestant's score by a fixed percentage; the latter is an additive bonus. Although total effort increases if the weak contestant is favored with a head start, the optimal use of handicaps is not as clear-cut. In one class of models it is profitable to handicap the strong contestant so severely that he will win less often than the weak contestant as a result. In another class of models it is profitable to handicap the weak contestant. When the contestants are sufficiently heterogenous and both instruments can be used, the weak contestant should be given a head start and a handicap. It is also possible to induce higher effort and at the same time make both contestants better off ex ante.

Game theory with costly computation: formulation and application to protocol security

Abstract: We develop a general game-theoretic framework for reasoning about strategic agents performing possibly costly computation. In this framework, many traditional game-theoretic results (such as the existence of a Nash equilibrium) no longer hold. Nevertheless, we can use the framework to provide psychologically appealing explanations to observed behavior in well-studied games (such as finitely repeated prisoner's dilemma and rock-paper-scissors). Furthermore, we provide natural conditions on games sufficient to guarantee that equilibria exist. As an application of this framework, we develop a definition of protocol security relying on game-theoretic notions of implementation. We show that a natural special case of this definition is equivalent to a variant of the traditional cryptographic definition of protocol security; this result shows that, when taking computation into account, the two approaches used for dealing with "deviating" players in two different communities-Nash equilibrium in game theory and zero-knowledge "simulation" in cryptography-are intimately related.