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on Economic Design |
| By: | Kemal Ozbek |
| Abstract: | We study optimal auction design in an independent private values environment where bidders can endogenously -- but at a cost -- improve information about their own valuations. The optimal mechanism is two-stage: at stage-1 bidders register an information acquisition plan and pay a transfer; at stage-2 they bid, and allocation and payments are determined. We show that the revenue-optimal stage-2 rule is the Vickrey--Clarke--Groves (VCG) mechanism, while stage-1 transfers implement the optimal screening of types and absorb information rents consistent with incentive compatibility and participation. By committing to VCG ex post, the pre-auction information game becomes a potential game, so equilibrium information choices maximize expected welfare; the stage-1 fee schedule then transfers an optimal amount of payoff without conditioning on unverifiable cost scales. The design is robust to asymmetric primitives and accommodates a wide range of information technologies, providing a simple implementation that unifies efficiency and optimal revenue in environments with endogenous information acquisition. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.07798 |
| By: | Junyao Zhao |
| Abstract: | In Bayesian single-item auctions, a monotone bidding strategy--one that prescribes a higher bid for a higher value type--can be equivalently represented as a partition of the quantile space into consecutive intervals corresponding to increasing bids. Kumar et al. (2024) prove that agile online gradient descent (OGD), when used to update a monotone bidding strategy through its quantile representation, is strategically robust in repeated first-price auctions: when all bidders employ agile OGD in this way, the auctioneer's average revenue per round is at most the revenue of Myerson's optimal auction, regardless of how she adjusts the reserve price over time. In this work, we show that this strategic robustness guarantee is not unique to agile OGD or to the first-price auction: any no-regret learning algorithm, when fed gradient feedback with respect to the quantile representation, is strategically robust, even if the auction format changes every round, provided the format satisfies allocation monotonicity and voluntary participation. In particular, the multiplicative weights update (MWU) algorithm simultaneously achieves the optimal regret guarantee and the best-known strategic robustness guarantee. At a technical level, our results are established via a simple relation that bridges Myerson's auction theory and standard no-regret learning theory. This showcases the potential of translating standard regret guarantees into strategic robustness guarantees for specific games, without explicitly minimizing any form of swap regret. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.03853 |
| By: | Shuyuan You; Zhiqiang Zhuang; Kewen Wang; Zhe Wang |
| Abstract: | Recent advances, such as RegretNet, ALGnet, RegretFormer and CITransNet, use deep learning to approximate optimal multi item auctions by relaxing incentive compatibility (IC) and measuring its violation via ex post regret. However, the true accuracy of these regret estimates remains unclear. Computing exact regret is computationally intractable, and current models rely on gradient based optimizers whose outcomes depend heavily on hyperparameter choices. Through extensive experiments, we reveal that existing methods systematically underestimate actual regret (In some models, the true regret is several hundred times larger than the reported regret), leading to overstated claims of IC and revenue. To address this issue, we derive a lower bound on regret and introduce an efficient item wise regret approximation. Building on this, we propose a guided refinement procedure that substantially improves regret estimation accuracy while reducing computational cost. Our method provides a more reliable foundation for evaluating incentive compatibility in deep learning based auction mechanisms and highlights the need to reassess prior performance claims in this area. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.13489 |
| By: | Bin Liu; Jingfeng Lu; Xianwen Shi |
| Abstract: | We study bilateral trade when private information arrives sequentially: the buyer learns her signal before the seller. In private values, this timing asymmetry restores efficiency: the efficient trade rule is implementable by a direct mechanism that is incentive compatible, exact budget balanced, and individually rational (interim for the buyer and ex ante for the seller). With interdependent values, efficiency can fail. We give primitive feasibility conditions and show that they hinge on how the seller’s cost responds to the buyer’s signal in the trading region. Allowing disclosure of the buyer’s report does not expand implementability. |
| Keywords: | Bilateral Trade, Mixed Participation, Efficiency, Disclosure |
| JEL: | D82 D61 |
| Date: | 2026–01–26 |
| URL: | https://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-816 |
| By: | Josué Ortega; Gabriel Ziegler; R. Pablo Arribillaga; Geng Zhao |
| Abstract: | The Deferred Acceptance (DA) algorithm is stable and strategy-proof, but can produce matchings that are Pareto-inefficient for students, and thus several alternatives have been proposed to correct this inefficiency that only involve consented priority violations. However, we show that these approaches cannot correct DA’s suboptimal rank distribution, because this shortcoming can arise even in cases where DA is Pareto-efficient. We also examine student segregation in settings with tiered priority structures. We prove that the demographic composition of every school is perfectly preserved under any Pareto-efficient rule that dominates DA, and consequently fully segregated schools under DA maintain their extreme homogeneity. |
| Keywords: | school choice, rank-efficiency, Rawlsian welfare, segregation |
| JEL: | C78 D47 |
| Date: | 2026–01–26 |
| URL: | https://d.repec.org/n?u=RePEc:bdp:dpaper:0089 |
| By: | Eugene Lim; Tzeh Yuan Neoh; Nicholas Teh |
| Abstract: | Envy-freeness up to any good (EFX) is a central fairness notion for allocating indivisible goods, yet its existence is unresolved in general. In the setting with few surplus items, where the number of goods exceeds the number of agents by a small constant (at most three), EFX allocations are guaranteed to exist, shifting the focus from existence to efficiency and computation. We study how EFX interacts with generalized-mean ($p$-mean) welfare, which subsumes commonly-studied utilitarian ($p=1$), Nash ($p=0$), and egalitarian ($p \rightarrow -\infty$) objectives. We establish sharp complexity dichotomies at $p=0$: for any fixed $p \in (0, 1]$, both deciding whether EFX can attain the global $p$-mean optimum and computing an EFX allocation maximizing $p$-mean welfare are NP-hard, even with at most three surplus goods; in contrast, for any fixed $p \leq 0$, we give polynomial-time algorithms that optimize $p$-mean welfare within the space of EFX allocations and efficiently certify when EFX attains the global optimum. We further quantify the welfare loss of enforcing EFX via the price of fairness framework, showing that for $p > 0$, the loss can grow linearly with the number of agents, whereas for $p \leq 0$, it is bounded by a constant depending on the surplus (and for Nash welfare it vanishes asymptotically). Finally we show that requiring Pareto-optimality alongside EFX is NP-hard (and becomes $\Sigma_2^P$-complete for a stronger variant of EFX). Overall, our results delineate when EFX is computationally costly versus structurally aligned with welfare maximization in the setting with few surplus items. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.12849 |
| By: | Debasis Mishra; Sanket Patil; Alessandro Pavan |
| Abstract: | We study procurement design when the buyer is uncertain about both the value of the good and the seller's cost. The buyer has a conjectured model but does not fully trust it. She first identifies mechanisms that maximize her worst-case payoff over a set of plausible models, and then selects one from this set that maximizes her expected payoff under the conjectured model. Robustness leads the buyer to increase procurement from the least efficient sellers and reduce it from those with intermediate costs. We also study monopoly regulation and identify conditions under which quantity regulation outperforms price regulation. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.08177 |
| By: | Joshua Kavner |
| Abstract: | Many multiagent systems rely on collective decision-making among self-interested agents, which raises deep questions about coalition formation and stability. We study social choice with endogenous, outcome-contingent transfers, where agents voluntarily form contracts that redistribute utility depending on the collective decision, allowing fully strategic, incentive-aligned coalition formation. We show that under consensus rules, individually rational strong Nash equilibria (IR-SNE) always exist, implementing welfare-maximizing outcomes with feasible transfers, and provide a simple, efficient algorithm to construct them. For more general anonymous, monotonic, and resolute rules, we identify necessary conditions for profitable deviations, sharply limiting destabilizing coalitions. By bridging cooperative and noncooperative perspectives, our approach shows that transferable utility can achieve core-like stability, restoring efficiency and budget balance even where classical impossibility results apply. Overall, this framework offers a practical and robust way to coordinate large-scale strategic multiagent systems. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.15563 |
| By: | Lixiong Li; Isma\"el Mourifi\'e |
| Abstract: | Counterfactual analysis is central to education market design and provides a foundation for credible policy recommendations. We develop a novel methodology for counterfactual analysis in Gale-Shapley deferred-acceptance (DA) assignment mechanisms under a weaker set of assumptions than those typically imposed in existing empirical works. Instead of fully specifying utility functions or students' beliefs about admission probabilities, we rely on interpretable restrictions on behavior that yield an incomplete but flexible model of preferences. This framework addresses the challenge of partial identification by delivering sharp bounds on counterfactual stable matching outcomes, which we compute efficiently using a combination of algorithmic techniques and integer programming. We illustrate the methodology by evaluating policies aimed at increasing female enrollment in STEM fields in Chile. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.08115 |
| By: | Sergiu Hart; Noam Nisan |
| Abstract: | We provide an elementary proof that revenue-maximizing mechanisms exist in multi-parameter settings whenever the distribution of valuations has finite expectation. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.01607 |
| By: | Kang Rong; Qianfeng Tang |
| Abstract: | We study surplus division in network constrained bilateral matching markets with transferable utility. We introduce a new solution concept, the credible bargaining solution, which refines stability by requiring that, for each matched pair of buyer and seller, surplus be divided according to the Nash bargaining solution with respect to credible outside options, defined as their payoffs in some stable outcome of the submarket obtained by removing their link. We establish general properties of the credible bargaining solution, prove existence, and provide a complete characterization in the unit-surplus case based on the notion of essential links. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.09198 |
| By: | Bossaerts, P.; Ioannidis, K.; Woods, R.; Yadav, N. |
| Abstract: | We study market equilibrium in settings with indivisible goods and tight budget constraints, where a traditional Walrasian Equilibrium (WE) may fail to exist. We introduce the Complexity Compensating Equilibrium (CCE), in which prices endogenously render the budget problem computationally difficult. Complexity induces heterogeneous demands even among agents with homogeneous preferences, as individuals allocate varying levels of cognitive effort. We define the equilibrium region as the set of price configurations that satisfy the necessary economic and computational conditions for equilibrium to exist. In this region, price configurations maximize the difficulty of the budget problem in addition to satisfying market clearing conditions. We evaluate the predictions of CCE through a controlled market experiment. We find that trading prices consistently force the budget problem to the equilibrium region. Further supporting and central to the CCE framework, the equilibrium bundles of goods generate markedly different utility levels across agents. This outcome contradicts a core feature of WE, namely, the equalization of utilities. In a setting where it exists, we reject WE on both prices and utilities, in favour of CCE. |
| Keywords: | General Equilibrium, Indivisibilities, Cognitive Effort, NP hard, Complexity Compensating Equilibrium, Walrasian Equilibrium, Markets Experiment |
| JEL: | D51 C92 C62 |
| Date: | 2026–01–02 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2603 |
| By: | Jiaming Wei; Dihan Zou |
| Abstract: | We study monopoly regulation under asymmetric information about costs when subsidies are infeasible. A monopolist with privately known marginal cost serves a single product market and sets a price. The regulator maximizes a weighted welfare function using unit taxes as sole policy instrument. We identify a sufficient and necessary condition for when laissez-faire is optimal. When intervention is desired, we provide simple sufficient conditions under which the optimal policy is a progressive price cap: prices below a benchmark face no tax, while higher prices are taxed at increasing and potentially prohibitive rates. This policy combines delegation at low prices with taxation at high prices, balancing access, affordability, and profitability. Our results clarify when taxes act as complements to subsidies and when they serve only as imperfect substitutes, illuminating how feasible policy instruments shape optimal regulatory design. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.06525 |
| By: | Keita Kuwahara |
| Abstract: | This note revisits the analysis of third-degree price discrimination developed by Bergemann et al. (2015), which characterizes the set of consumer-producer surplus pairs that can be achieved through market segmentation. This was proved by means of market segmentation with random prices, but it was claimed that any segmentation with possibly random pricing has a corresponding direct segmentation, where a deterministic price is charged in each market segment. However, the latter claim is not correct under the definition of market segmentation given in the paper, and we provide counterexamples. We then propose an alternative definition to resolve this issue and examine the implications of the difference between the two definitions in terms of the main result of their paper. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.07452 |