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Stable matchings in school choice needn’t be Pareto efficient and can leave thousands of students worse off than necessary. Call a matching μ priority-neutral if no matching can make any student whose priority is violated by μ better off without violating the priority of some student who is made worse off. Call a matching priority-efficient if it is priority-neutral and Pareto efficient. We show that there is a unique priority-efficient matching and that it dominates every priority-neutral matching and every stable matching. Moreover, truth-telling is a maxmin optimal strategy for every student in the mechanism that selects the priority-efficient matching.

A game is better-reply secure if for every nonequilibrium strategy x* and every payoff vector limit u* resulting from strategies approaching x*, some player i has a strategy yielding a payoff strictly above u*i even if the others deviate slightly from x*. If strategy spaces are compact and convex, payoffs are quasiconcave in the owner's strategy, and the game is better-reply secure, then a pure strategy Nash equilibrium exists. Better-reply security holds in many economic games. It also permits new results on the existence of symmetric and mixed strategy Nash equilibria.

Citation indices are regularly used to inform critical decisions about promotion, tenure, and the allocation of billions of research dollars. Nevertheless, most indices (e.g., the h-index) are motivated by intuition and rules of thumb, resulting in undesirable conclusions. In contrast, five natural properties lead us to a unique new index, the Euclidean index, that avoids several shortcomings of the h-index and its successors. The Euclidean index is simply the Euclidean length of an individual's citation list. Two empirical tests suggest that the Euclidean index outperforms the h-index in practice.

We generalize Athey's (2001) and McAdams' (2003) results on the existence of monotone pure-strategy equilibria in Bayesian games. We allow action spaces to be compact locally complete metric semilattices and type spaces to be partially ordered probability spaces. Our proof is based on contractibility rather than convexity of bestreply sets. Several examples illustrate the scope of the result, including new applications to multi-unit auctions with risk-averse bidders.

For an arbitrary data set D = {(p, x)} ⊂̠ (ℝm+\\{0}) × ℝm+, finite or infinite, it is shown that the following three conditions are equivalent: (a) D satisfies GARP; (b) D can be rationalized by a utility function; (c) D can be rationalized by a utility function that is quasiconcave, nondecreasing, and that strictly increases when all its coordinates strictly increase. Examples of infinite data sets satisfying GARP are provided for which every utility rationalization fails to be lower semicontinuous, upper semicontinuous, or concave. Thus condition (c) cannot be substantively improved upon.

Consider the problem of maximizing the revenue from selling a number of goods to a single buyer. We show that, unlike the case of one good, when the buyer's values for the goods increase the seller's maximal revenue may well decrease. We then identify two circumstances where monotonicity does obtain: when optimal mechanisms are deterministic and symmetric, and when they have submodular prices. Next, through simple and transparent examples, we clarify the need for and the advantage of randomization when maximizing revenue in the multiple-good versus the one-good case. Finally, we consider \"seller-favorable\" mechanisms, the only ones that matter when maximizing revenue. They are essential for our positive monotonicity results, and they also circumvent well-known nondifferentiability issues.

We provide several generalizations of the various equilibrium existence results in Reny (Econometrica 67:1029–1056, 1999), Barelli and Meneghel (Econometrica 81:813–824, 2013), and McLennan et al. (Econometrica 79:1643–1664, 2011). We also provide an example demonstrating that a natural additional generalization is not possible. All of the theorems yielding existence of pure-strategy Nash equilibria here are stated in terms of the players' preference relations over joint strategies. Hence, in contrast to much of the previous work in the area, the present results for pure-strategy equilibria are entirely ordinal.

We extend Kreps and Wilson’s concept of sequential equilibrium to games with infinite sets of signals and actions. A strategy profile is a conditional ε-equilibrium if, for any of a player’s positive probability signal events, his conditional expected utility is within ε of the best that he can achieve by deviating. With topologies on action sets, a conditional ε-equilibrium is full if strategies give every open set of actions positive probability. Such full conditional ε-equilibria need not be subgame perfect, so we consider a non-topological approach. Perfect conditional ε-equilibria are defined by testing conditional ε-rationality along nets of small perturbations of the players’ strategies and of nature’s probability function that, for any action and for almost any state, make this action and state eventually (in the net) always have positive probability. Every perfect conditional ε-equilibrium is a subgame perfect ε-equilibrium, and, in finite games, limits of perfect conditional ε-equilibria as ε → 0 are sequential equilibrium strategy profiles. But limit strategies need not exist in infinite games so we consider instead the limit distributions over outcomes. We call such outcome distributions perfect conditional equilibrium distributions and establish their existence for a large class of regular projective games. Nature’s perturbations can produce equilibria that seem unintuitive and so we augment the game with a net of permissible perturbations.