4,271 papers in this slice of arXiv.
Constantine Sorokin, Alexander Nesterov, Alexei Savvateev
In organized crime, membership moves fastest, deterrence capacity moves more slowly, and division norms move slowest. We model this as a three-stage game: division norms fix how every possible coalition divides its proceeds; the authority then attaches deterrence capacity to named members, before knowing which coalition will form; membership adjusts last, around whoever remains undeterred. Under population-monotone division, the minimum deterrence budget is the cost of a shortest dismantling path, removing one member at a time. When the Shapley value is population monotone, it uniquely maximizes this budget by making every path equally costly.
R. B. Bapat, Debapriya Sen
We solve a natural bimatrix game related to graphs. We consider a finite directed graph G=(V,E), where the strategy set of Player I is the set of vertices V and that of Player II is the set of edges E. There are two sets of positive weights {αe}e∈E and {βe}e∈E. If Player I chooses a vertex v and Player II chooses an edge e, then the payoff to both players is zero if v and e are not incident. If e originates from v, then Player I obtains αe and Player II obtains −βe. If e terminates at v, then Player I obtains −αe and Player II obtains βe. For this game the payoff matrices are weighted incidence matrices of the graph G. We show that when the graph is acyclic, Player I has a unique strategy in any equilibrium. At this strategy, every vertex is chosen with a probability that is proportional to the maximum length over all directed paths originating from that vertex. Defining the path matrix of the graph, it is shown that the set of all equilibrium strategies of Player II is the convex hull of the column vectors of the path matrix. This work extends earlier results of Bapat and Tijs (1997) for zero-sum games.
Harry Kleyer
This paper studies imperfect competition in general equilibrium when households and firms choose price-contingent schedules. Market clearing selects the price generated by those schedules, and each agent accounts for how its own behavior changes equilibrium prices. We derive household and firm optimality conditions, establish existence and a trembling-hand refinement, and apply the framework to monopoly, vertical market power, entry, ownership, and technological change. The results show that endogenous price responses can change standard conclusions about markups, deadweight loss, firm creation, and investment.
Raphael Boleslavsky, Thomas Jungbauer, Mehdi Shadmehr
We study a platform that prefers to sell the more profitable of two products. It designs an algorithm that determines the product the consumer encounters first, conditional on her best match. The algorithm simultaneously manipulates consumer attention (steers) and communicates information about match quality (informs). When the algorithm is opaque, it is difficult for a consumer to understand how product order is generated and what it reveals. In the platform's preferred equilibrium, it places the profitable product first. When the algorithm is transparent, the consumer understands the algorithm and what it conveys. Thus, the algorithm can persuade as well as steer. In some cases, the equilibrium algorithm deters search, in others, encourages it. In the former case, transparency helps consumers; in the latter, it harms some or all of them. Extending or shifting transparency requirements uncouples steering from information provision, reverting the consumer's welfare to opacity.
Kevin A. Bryan, Joshua S. Gans
AI predicts; humans use its predictions to make decisions. These predictions are combined with human verification and analysis, queries to other statistical models, and so on. The economic value of an AI, therefore, depends on how it interacts with the surrounding decision environment. We describe the value of AI as part of this ``composite experiment'' where AI makes a coarse prediction of the state of the world, show what this means for optimal model training via a geometric argument, explain why optimal training can be discontinuous in economic variables, and study how heterogeneous users or monopoly model trainers affect these results. In particular, maximizing the unconditional accuracy of AI predictions is generally suboptimal.
Itai Ashlagi, Joseph Root
We study two observable queues with identical service rates, serving agents who arrive stochastically over time. Agents join the queue that minimizes their expected waiting time. Assuming one queue uses the ubiquitous First-Come-First-Served (FCFS) service rule, we show that by simply modifying its service order, the other queue can capture a strict majority of the demand. We establish an upper bound on the arrival share any rule can capture against FCFS. When both queues can design their service order, we show a novel variant of Last-Come-First-Served (LCFS) is an equilibrium in a low congestion regime. Without commitment, the picture changes, and there is an equilibrium where both queues use FCFS, and agents route to the queue with the shorter waitlist.
Meina Takahashi
We extend the concept of priority-neutral matching, introduced by Reny (2022) in the school choice context, to the roommate problem. We prove three main results. First, a blocking-neutral matching always exists in constrained roommate problems under arbitrary feasibility constraints (Theorem 1). Second, the set of stable matchings is contained in the set of blocking-neutral matchings, which in turn is contained in the set of Pareto-optimal matchings (Theorem 2). Third, whenever stable matchings exist, the set of blocking-neutral matchings coincides with the set of stable matchings (Theorem 3). We also show that existence fails under weak preferences and extend the concept to two-sided school choice.
Nicholas Teh
Full justified representation (FJR) is among the strongest known satisfiable proportionality axioms for approval-based committee elections. Recent work has shown that an FJR committee can be found in polynomial time, but verifying whether a given committee satisfies FJR remains coNP-complete. We introduce FJR+, a strict strengthening of FJR and EJR+ that can be verified and satisfied in polynomial time. We then analyze the Residual-Budget Greedy (RBG) algorithm and prove that it selects a partial committee such that every size-k completion satisfies FJR+. This freedom allows us to use sequential Phragmén to obtain a priceable completion. The resulting rule always satisfies FJR+ and the sub-core, and it is priceable whenever at least k candidates receive an approval. We also obtain a Droop-quota version of FJR+. Finally, we extend FJR+ to approval-based participatory budgeting with arbitrary project costs. A project-specific version of RBG computes this property in polynomial time and can be continued to a priceable outcome satisfying a cost-based version of the sub-core.
Federico Echenique, Teddy Mekonnen, M. Bumin Yenmez
How should institutions compare group diversity, and which group should they select when they value diversity and merit? We take a target-based approach that evaluates the entire group composition without treating any type as intrinsically diversity-enhancing. Because different diversity indices may rank groups differently, we instead adapt majorization to construct an ordinal diversity preorder. We show that its maximally diverse selections are exactly those maximizing every index in a broad class. This characterization yields a reserve-and-quota policy that selects a maximally diverse group and, among such groups, the highest-merit agents. Any alternative is less diverse, less meritorious, or both.
Azar Aliyev
A number of recent empirical papers rely on a collective model to analyze the portfolio choice of spouses, their heterogeneous risk preferences, and intra-household bargaining. I study applications of this model and highlight some important shortcomings. In its classic form, the model generates a counterintuitive result: an increase in the risk aversion of a household member can lead to an increase in household risk-taking. I offer a formal characterization of this pattern and link it to previous theoretical findings. I highlight further issues with applications of the collective approach to the portfolio choice problem in the contexts of bargaining and wealth inequality. I reconcile recent household finance papers with these findings and point to potential confusion in the literature. I emphasize existing alternatives that do not exhibit most of these issues, yet argue that there is a lack of a consistent and rigorous modeling approach.
Carl-Christian Groh
What determines the speed and direction of AI learning? I analyse this question from a microeconomic perspective by studying a model in which AI providers sell access to users who must complete tasks using either AI or labor. Users differ in the share of complex tasks they face. When complex tasks are delegated to AI, it learns to perform them better. In an initial technological state where AI has a comparative advantage at easy tasks, users with many complex tasks have low willingness to pay for access. This gives rise to a tension between profit maximization and complex-task learning. I characterize when this tension gives rise to a convex path of labor displacement or a learning trap in a monopoly benchmark. Competition between AI providers increases the speed of labor displacement if it is intense. Asymmetric competition can increase the speed of labor displacement by promoting endogenous specialization of AI providers.
Mark Whitmeyer
Every statistic on laws with finite pth moment that is additive across independent risks and monotone in mean-preserving spreads depends only on an additive function of the mean when p is strictly less than 2, and only on such a function and a nonnegative multiple of the variance when p is no less than 2.
Vilok Taori
A principal seeks to allocate k identical objects among n sequentially arriving, impatient agents. Each agent privately observes her valuation, and the principal's payoff from allocating an object depends on the recipient's valuation. The principal can perfectly verify the valuation of at most m agents, where m<k, and commits to a mechanism before any agent arrives. We characterize the class of optimal mechanisms. Our main result establishes that, in states where the number of remaining objects exceeds the number of available verification checks, the optimal mechanism may involve probabilistic verification.
Yuliy Sannikov, Weijie Zhong
We study a decision-maker who explores --- dynamically choosing what to learn --- before stopping to act. We first reduce this dynamic control problem to a static one: any exploration-and-stopping strategy is equivalent to a choice of the joint distribution of the stopped state and the stopping time, subject to one information-budget constraint at each date, and we characterize exactly which distributions are attainable. The reduced problem is a convex program with a linear objective; its dual prices information over time, and the optimal policy concavifies the stopping payoff net of these shadow prices. The curvature of the decision-maker's time preference then governs the shape of optimal exploration: convex time preference induces Poisson exploration, concave time preference confines stopping to a window whose length is controlled by the dispersion of the marginal cost of delay --- forcing an initial phase of pure exploration when the window is short --- and the linear case lies at the boundary between them. We apply the framework to real options, to the speed--accuracy tradeoff in information acquisition, and to a continuous-time exploration contest.
Grzegorz Jamróz
Inspired by possible future markets of autonomous routing and driving (ARAD), we introduce competitive mediator games and their equilibria which generalize the (coarse) correlated equilibria, which have become a popular research area recently as they not only can be more socially efficient than Nash equilibria but also are limits of algorithmic no-regret multi-agent learning dynamics. We discuss the basic properties of competitive mediator games and prove that in the generic setting of anonymous congestion(routing) games with market-share maximizing mediators all competitive mediator equilibria are monopolies whenever one of the mediators is weakly preferred to other mediators by all users. We apply and interpret these results in the context of new markets of competing ARAD service providers. We also provide a comprehensive overview of these markets and discuss the future mechanism design thereof.
Jiangtao Li, Rui Tang, Mu Zhang
We present a model of associative networks that captures how decision makers expand their consideration set through mental associations between alternatives. Our model provides a tractable approach to study how associations shape choice when some alternatives are available and others are merely observable but unavailable. We characterize the model within a random attention framework and demonstrate unique identification of all parameters. This framework delivers a unified account of several prominent choice anomalies, including classic menu effects and their ``phantom'' counterparts. We illustrate how associative links serve as a strategic variable in applications such as branding, imitation, and platform design.
Deniz Kattwinkel, Alexander Winter
A principal must decide whether to implement a project. She privately knows the cost, an agent privately knows the benefit. Monetary transfers are not available, and compared to the principal, the agent does not fully internalize the cost. We show that the principal-optimal mechanism does not require the agent to report. Instead, it either ignores the agent or endows the agent with free information and full decision authority.
G. Charles-Cadogan
We develop a behavioural model of bank run exposure in a paycheck-to-paycheck economy with loss averse depositors. Income is received through demand deposits, and consumption ratcheting embeds reference dependence in a parsimonious asset-pricing framework. We show that sufficiently high subjective bad-state probabilities endogenously increase liquidity demand and generate equilibrium stress states supporting bank runs. These states define a Bank Run Exposure State Space and yield a martingale representation for exposure dynamics. A proof-of-concept empirical implementation using Call Report data constructs bank-level exposure proxies from funding and lending composition. A regression-weighted composite measure modestly improves fit relative to a retail-share benchmark, with stronger amplification among small banks and during the post-Silicon Valley Bank (SVB) collapse period. The framework highlights how behavioural liquidity demand alters equilibrium reserve holdings and can crowd out productive lending.
Gregorio Curello, Sam Jindani
We consider the problem of bargaining when transfers between agents are possible. Such situations are typically modelled as coalitional games with transferable utilities. However this model makes a strong implicit assumption: the outcome can only depend on the total surplus that each coalition of agents can achieve, not on which agents within the coalition generate the surplus. Is this assumption justified? We define a richer model in which solutions may depend on who generates the surplus. In this model, the classical axiomatisation of the Shapley value fails: a broad family of solutions satisfy efficiency, anonymity, the dummy property, and additivity. Nevertheless, we obtain an axiomatisation of the Shapley value in the richer model by adding continuity and a strengthening of the dummy property to the original axioms.
Wesley H. Holliday
A common problem in social choice is to determine whether there is a social choice procedure, such as a voting method, satisfying some desired criteria. Computer-aided methods such as SAT solving can sometimes answer these questions. However, under typical encodings, a SAT solver may only synthesize a voting method on a finite domain, while we may want one on an infinite domain, such as the domain of all preference profiles for a fixed number of candidates but any finite number of voters. In this paper, we use an approach based on reasoning with constrained Horn clauses and computation with polyhedra to synthesize a voting method on an infinite domain. We then use SMT and Lean to verify its properties. Our main result is a possibility theorem about four well-known criteria from voting theory: the Condorcet winner and loser criteria, positive involvement, and resolvability. Previous work has shown that for five or more candidates, there is no voting method satisfying these axioms, and that for four candidates, there is no method satisfying these core axioms plus one more invariance axiom. Here we show that for four candidates, there does exist a method satisfying the core axioms and more.