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on Economic Design |
| By: | Salvador Candelas; Nicole Immorlica; Brendan Lucier |
| Abstract: | We study markets where firms compete for consumer attention by subsidizing costly product inspection. These subsidies do not change product quality, but they alter the order in which consumers search by lowering inspection costs. We establish a subsidy-sorting principle: in any equilibrium, higher-quality firms provide weakly larger subsidies, leading consumers to search in descending subsidy order. A unique equilibrium survives forward-induction reasoning in the spirit of the Intuitive Criterion: low-quality firms are never inspected, intermediate-quality firms separate with strictly increasing subsidies, and high-quality firms pool at the full subsidy. This equilibrium maximizes information revelation among all possible outcomes and ensures efficient inspection. We then extend the analysis to AI-mediated platforms that can create and price inspection tokens. The platform's optimal linear pricing leads to excessive inspection relative to the social optimum. While this distortion does not reduce consumer welfare, it reallocates surplus from sellers to the platform and consumers. |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2605.28985 |
| By: | Lauri Lov\'en; Sujit Gujar; Kalle Timperi; Hassan Mehmood; Praveen Kumar Donta; Sasu Tarkoma; Schahram Dustdar |
| Abstract: | Mechanism-mediated service markets with polymatroidal feasibility admit efficient, dominant-strategy incentive-compatible (DSIC) allocation, but these guarantees implicitly assume truthful execution by the marketplace operator. Modelling the operator as a strategic player, we establish a credibility trilemma: for single-parameter agents on a non-modular polymatroid, no static sealed-bid mechanism is simultaneously revenue-optimal, DSIC for agents, and credible for the operator. We introduce the Cost of Non-Credibility (CoNC) as a price-of-anarchy-style welfare-loss measure and obtain tight $\Theta$-bounds across five topology classes (single-edge, series, parallel, tree, series-parallel), plus a matching upper bound $O(|\mathcal{S}|)$ on general DAGs realised by an $\Omega(|\mathcal{S}|)$ witness on the SP-augmented sub-family, turning the trilemma into a structural quantity. Three structurally distinct resolutions follow: public broadcast or deferred-revelation commitment, administrative domain separation under settlement separation and four side conditions, and integrator competition orthogonal to mechanism execution under disjoint actors. An instance-level grounding over the edge-pricing market of Amin et al. confirms the trilemma's robustness on a refereed external setting. The result establishes marketplace neutrality as a first-order design constraint on polymatroidal service markets rather than an implementation detail: where the operator is a strategic player, credibility trades off against revenue optimality and agent incentive compatibility along structurally characterised lines. |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2605.26604 |
| By: | Billimoria, F.; Simshauser, P. |
| Abstract: | This article examines the design and valuation of cap-and-floor hedge contracts in hybridised electricity markets, with a focus on their interaction with merchant price risk and project finance structures. Cap-and-floor or 'collar' mechanisms have emerged as a prominent policy instrument to support long-duration storage and firming investment by enhancing project bankability. We show that when investments are financed under leveraged project finance constraints, the value of a profit -sharing collar contract is driven primarily by its ability to truncate left-tail revenue risk rather than its risk -neutral fair value. As a result, collars are likely to be provided to investors at prices that differ materially from actuarial fair valuations in order to meet financing requirements. Incorporating imperfect foresight and empirically calibrated heavy-tailed price forecast errors, we demonstrate that downside dispersion plays a central role in determining debt sizing and investment incentives. Moreover, by examining re-contracting potential, we find the presence of centrally provided profit -sharing collars may materially reduce participant incentives to participate in forward derivative markets, weakening one of the commonly cited advantages of the structure. Overall, it emphasises the importance of transparent contract valuation and careful hedge market design in hybridised electricity markets. |
| Keywords: | Electricity Markets, Risk Trading, Project Finance, Contract Design, Energy Storage |
| JEL: | D47 D52 D53 G12 Q40 |
| Date: | 2026–05–31 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2640 |
| By: | Yuxin Liu; M. Amin Rahimian |
| Abstract: | Information sharing among competing suppliers can improve decision-making under uncertainty, yet strategic concerns regarding rival exploitation often deter voluntary disclosure. We study information-sharing mechanisms in a Cournot oligopoly with uncertain demand, where a platform aggregates suppliers' signals through privacy-preserving channels and may also possess an exogenous external signal. The central challenge is to balance strategic safety with informational utility: privacy noise reduces the exposure of individual signals, but also lowers the value of the shared information pool. We first characterize a baseline setting in which access to aggregated information is contingent on participation. In a two-firm market without an external signal, firms refuse to share regardless of the privacy level. In an \(n\)-firm market, sharing may arise even without privacy safeguards because non-participating firms lose access to the aggregated signal. Building on this baseline, we show that privacy protection alone is insufficient to incentivize disclosure; it must be combined with a sufficiently informative external signal. We further show that firms with more accurate private signals require stronger privacy protection. Overall, our results characterize the sharing-feasible region and highlight the complementarity between privacy design and the external information environment. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2606.02348 |
| By: | Haijing Zong; Yancheng Liang; Boyang Zhou; Natasha Jaques |
| Abstract: | Two-sided matching markets often involve information that unfolds over time through interviews, repeated interaction, learning, and separation. Existing matching models typically reduce this process to immediate sub-Gaussian feedback about fixed preferences, missing settings where payoff-relevant information is revealed gradually and changes future matching decisions. We introduce a framework with temporally extended feedback, that formulates two-sided matching as a partially observable Markov game with costly pre-match screening, noisy post-match observations, evolving latent profiles, and endogenous continuation or dissolution. We instantiate this framework in Learn2Match, a multi-agent reinforcement-learning benchmark for dynamic matching markets. Learn2Match supports decentralized decision making over whom to interview, whom to match with, and when to dissolve a match, while evaluating policies using regret, social welfare, and an information-friction loss that measures the welfare gap caused by incomplete revelation of latent preferences. We find that independent PPO achieves higher cumulative social welfare and lower cumulative regret than the bandit-style CA-ETC baseline under temporally extended feedback, demonstrating the promise of MARL for dynamic matching markets. However, PPO still incurs higher information-friction loss, revealing that end-to-end MARL does not yet provide the coordinated exploration structure of matching-bandit methods. These results position Learn2Match as a benchmark for developing the next generation of matching-market algorithms: methods that are adaptive like RL agents, statistically disciplined like bandit algorithms, and structurally aware like stable-matching mechanisms. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2606.06744 |
| By: | Satoru Fujishige; Leo Goto; Satoshi Nakada |
| Abstract: | We propose a new voting algorithm based on the pairwise majority-comparison matrix derived from voters' preference profiles. We show that this algorithm induces exactly the winner set of the Schulze rule (Schulze, 1997). Our algorithm successively eliminates weaker candidates in terms of all-pairs comparisons, thereby reflecting a dual spirit to Condorcet's original idea of splitting preference cycles (de Condorcet, 1785). We further show that the direct sum of the survival sets obtained at each elimination round coincides with the Schwartz set (Schwartz, 1972). These two equivalence results provide a formal mathematical foundation for the ``folklore'' relationship between the Schulze winner set and the Schwartz set, as well as a new Condorcetian interpretation of the Schulze winner set. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2606.02213 |
| By: | Anisha Bandyopadhyay; Sinan Ertemel; Rajnish Kumar; Saptarshi Mukherjee |
| Abstract: | We study the problem of allocating a finite estate among agents whose total claims exceed the available resources, a standard framework in the theory of claims problems. Two canonical rules embody competing fairness ideals: the Proportional rule allocates in proportion to claims, while the Constrained Equal Awards (CEA) rule equalizes awards as much as possible subject to claim-boundedness. We introduce the P-CEA family of compromise rules, which assigns each agent a fixed baseline award, capped by her claim, and distributes the remaining estate proportionally to residual claims. By varying the baseline parameter, this family generates a continuum of allocation rules that interpolates between the Proportional and CEA benchmarks. We provide an axiomatic characterization based on two threshold-dependent principles: No Advantageous Reallocation, which prevents agents with claims above the threshold from benefiting through coordinated claim redistribution that preserves the threshold condition, and Sustainable Lower Bound, which guarantees each agent at least the minimum of her claim and the threshold. We further develop a dual analysis that reallocates losses instead of awards and characterize the corresponding dual family using the dual versions of our axioms. |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2605.26948 |
| By: | Pieroni, Luca; Roig, Melcior Rossellò |
| Abstract: | This paper studies the ex ante design of costly reform architectures. Before the welfare environment is realised, an institution chooses a directed graph of admissible public reasons over a finite set of institutional meanings. Re form proceeds along maintained edges via welfare non-decreasing steps. The main result characterises reform completeness through a trap-cut condition: the architecture must contain a welfare-improving exit from every upper-contour trap. On the unrestricted welfare domain this forces the complete directed graph; on a tree-single-peaked domain the unique minimum-cost architecture is the bidirected tree, reducing the language from quadratic to linear. Under ambiguity about the domain, only three architectures are optimal—no costly language, the bidirected tree, or the complete graph—and the sparse intermediate regime collapses discontinuously to the complete language above a critical ambiguity threshold. The analysis extends to finite lattices, where the bidi rected cover graph is the unique minimum-cost architecture for domains with cover-connected upper contours. |
| Keywords: | public reasons; institutional design; reform; single-peakedness; graph theory; costly language; path dependence; lattice. |
| JEL: | C61 C72 C78 D71 D83 |
| Date: | 2026–05–19 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:129163 |
| By: | Yakov Babichenko |
| Abstract: | A decision-maker (DM) repeatedly makes choices under uncertainty in a bandit environment, where only the realization of the chosen arm is observed. Another competing agent, the adviser (AD), repeatedly provides recommendations, but the realizations of these recommendations are unobserved unless they coincide with the DM's choice. Both agents possess partial information about the arms' realizations. The central question we focus on is whether, in the long run, an outside observer can identify which agent is more informed based solely on the observed decisions, recommendations, and arm realizations. A test selects one of the agents based on the observed data. We focus primarily on the class of scoring tests, which assign a numerical score to each observation and select the agent according to the average score. We study strategic agents whose objective is to be selected by the test. For simultaneous arm choices, we show that there exists a scoring test that successfully identifies the more-informed agent. For sequential arm choices, however, no such scoring test exists. Finally, we explore the tension between identifying the more-informed agent and maximizing welfare. A DM whose objective is to pass the test may not necessarily make welfare-maximizing decisions. In a binary-arm environment, we show that no scoring test can simultaneously identify the more informed agent and achieve more than half of the welfare attained by welfare-maximizing decisions. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2606.02095 |
| By: | Alireza Soltani; David M. Levinson; Mohsen Ramezani (TransportLab, School of Civil Engineering, University of Sydney) |
| Abstract: | This paper introduces a novel approach for managing autonomous vehicles at signal-free intersections through a Communication-free Distributed Control Algorithm (CfDCA). Unlike centralized systems or communication-based decentralized methods, CfDCA relies solely on onboard sensors and in-vehicle decision-making to ensure efficient and collision-free navigation. The algorithm formulates intersection management as a distributed optimization problem with demonstrated safety logics and robustness to measurement errors. The algorithm combines a dynamic resource acquisition graph with a refined priority function and an adaptive tolerance mechanism to ensure efficient performance under varying traffic conditions. A stochastic tiebreaking mechanism is proposed to handle rare cases of identical priorities, while deadlock prevention is guaranteed through strict priority ordering. Simulation experiments demonstrate that CfDCA reduces average delay and queue length and is able to achieve throughput higher than actuated signalized intersections and outperforms a first-come-first-served baseline in delay reduction. Additionally, the algorithm’s distributed design offers scalability and eliminates dependency on communication infrastructure. |
| Keywords: | transportation, road transport, automated vehicles |
| JEL: | R40 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:nex:wpaper:paper-2025-10 |
| By: | Alexander Matros (University of South Carolina); Constantine Sorokin (University of Glasgow) |
| Abstract: | We study a tractable two-player contest built on a truncated cubic contest success function. Its defining feature is a strategic-feedback parameter whose sign determines whether a leading player's effort lowers (suppression) or raises (empowerment) the marginal effectiveness of the trailing player's effort; standard lottery contests impose suppression by construction. The benchmark yields closed-form mixed equilibria under complete information and a unique affine Bayesian Nash equilibrium under IID private information. Expected effort is typically single-peaked in the feedback parameter. Uncertainty lowers effort under suppression but raises it under empowerment, and the same asymmetry governs information disclosure: an effort-maximizing designer withholds information under suppression and discloses fully under empowerment. Several familiar conclusions of contest theory turn out to reflect suppressive benchmarks rather than contests as such. |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2605.26639 |