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on Economic Design |
| By: | Kohmei Makihara |
| Abstract: | We study how to allocate a good with positive externalities among agents in an information network, without monetary transfers. Each agent observes their own valuation and those of their neighbors. A principal seeks to allocate the good to the highest-valuation agent through a mechanism robust to agents' heterogeneous belief hierarchies, leveraging the network structure and the partial incentive alignment created by allocative externalities. We characterize the networks for which a robustly efficient mechanism exists: it exists if and only if at least two agents are connected to all others. Relaxing robustness to rule out weakly dominated strategies, one universally connected agent suffices. We generalize the results to a broader class of utility functions, show that robust welfare maximization is impossible unless the network is complete, and establish that an ex post incentive compatible mechanism that is efficient under truthful reports exists if and only if no agent is isolated. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.35907 |
| By: | Yasushi Kawase |
| Abstract: | We study the reallocation of indivisible objects among agents who may hold initial endowments and may be indifferent between objects. Each agent has her own set of admissible objects, and a matroid constraint specifies which combinations of assigned objects are feasible. The model contains the housing market, house allocation with newcomers who hold no endowment, and the assignment of students to schools under matroidal constraints at each school. For this model, we introduce the top-class trading cycles mechanism (TCTC), which extends the top trading cycles mechanism (TTC) to matroid constraints and weak preferences. When a trading cycle is selected, TCTC fixes each agent's top indifference class rather than a specific object and postpones the choice within the class to the end. TCTC is individually rational, Pareto efficient, and weakly group-strategy-proof on the full domain of weak preferences, and it runs in polynomial time. When preferences and reports are strict, TCTC is strongly group-strategy-proof. Together with a known impossibility result, our theorem establishes a maximal domain of school-by-school constraints for individual rationality, Pareto efficiency, and strategy-proofness. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.32337 |
| By: | Guoqiang Tian |
| Abstract: | This paper studies the endogenous informational evolution of dynamic economic systems. Building on Hurwicz's conceptual framework, such a system is defined as a dynamic joint adjustment process of resource and information allocation linked by recursive feedback. Economic theory gains precision by isolating particular margins, but when information production, disclosure, learning, incentives, actions, and future feasibility interact across these two processes, conclusions obtained by holding other margins fixed need not survive their joint determination. The paper develops a system-level dynamic equilibrium framework for this interaction. Holding particular links fixed yields familiar environments in dynamic mechanism design, information design, experimentation and learning, feedback and disclosure, and information acquisition. The analysis establishes three central failures relative to fixed or partially exogenous informational environments: informational efficiency under exogenous feasibility is generally incompatible with endogenous dynamic feasibility; incentive and disclosure design cannot generally be separated; and informational monotonicity can fail without implementation replicability. It also identifies the corresponding positive boundaries. Optimal disclosure may be interior or extreme; bang--bang disclosure arises under additional conditions, and a further specialization generates an endogenous transition from opacity to transparency. Information may therefore be optimally withheld even when its direct decision value is strictly positive. Extensions to private payoff-relevant information and limited commitment preserve the recursive structure. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.36093 |
| By: | Hinata Kurashita |
| Abstract: | We study object reallocation problems with single-peaked preferences. On the unrestricted domain of strict preferences, top trading cycles (TTC) is the unique rule that satisfies efficiency, individual rationality, and strategy-proofness. On the single-peaked preference domain, the crawler introduced by Bade (2019) satisfies the same properties. We show that the Nash equilibrium allocations of the crawler's direct revelation game form a complete lattice under weak Pareto dominance. The truthful allocation is the greatest element of this lattice, while the initial endowment allocation is its least element. |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.08096 |
| By: | Olivier Bos; Martin Pollrich |
| Abstract: | We study mechanisms in which agents' preferences depend both on an object allocation and on a third party's beliefs about private information. A mechanism determines an allocation, transfers, and sends signals to the aftermarket. We compare two informational environments: (i) private transfers, where the aftermarket observes allocations and signals, and (ii) public transfers, where transfers are publicly observable. Our main result shows that any equilibrium outcome implementable with hidden transfers can be approximated arbitrarily well with public transfers. Thus, transfer observability generates at most a vanishing informational distortion and helps rationalize the common assumption that transfers remain hidden from aftermarkets. |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.03146 |
| By: | Hao Yu |
| Abstract: | When a subset of alternatives is allowed to be the collective choice, one approach is to study the social choice correspondence defined on agents' preferences over alternatives. This paper considers a different approach. We argue that agents should have preferences directly over outcomes. We consider the social choice problem on a closed real interval, and assume a single-peaked domain over intervals. Our focus is on the peak-only social choice function, referred to as the voting scheme. The leftright scheme, which generalizes the minmax scheme, is the only strategy-proof voting scheme. Adding anonymity, it reduces to the generalized median scheme. For an odd number of agents, the median scheme is the only voting scheme satisfying efficiency, anonymity, and strategy-proofness. |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.08435 |
| By: | Carmelo Rodríguez à lvarez (ICAE Instituto Complutense de Análisis Económico, Depto. Análisis Económico y Economía Cuantitativa, Universidad Complutense de Madrid) |
| Abstract: | We study social choice functions that select sets of alternatives, taking voters' preferences over sets as input, when voters evaluate sets according to conditional expected utility obtained from Bayesian updating of a prior. Barberà et al. (2001) shows that under a uniform common prior both dictatorial and bidictatorial rules satisfy strategy-proofness and unanimity. We show that this multiplicity is a knife-edge case. If at most one voter holds a uniform initial prior, dictatorship is the unique rule satisfying these properties. The argument links set-valued rules to random dictatorship and shows that the probability ratios imposed by Bayesian updating from non-uniform priors are incompatible with combining the top choices of multiple voters. |
| Keywords: | Strategy-proofness; Social choice functions over sets; Random dictatorship; Probability assessments. |
| JEL: | C71 D82 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ucm:doicae:2602 |
| By: | Parinaz Naghizadeh; Jingyan Wang |
| Abstract: | In school choice, a lottery number is often used by the matching mechanism to break ties when there are more students who prefer the same school than the number of seats available. There has been growing theoretical and empirical interest in understanding the impact of revealing the lottery number to students. In practice, in recent years, the NYC Public Schools started revealing the lottery number to students to improve transparency. Theoretical findings from prior literature also suggest that revealing the lottery number strictly improves the number of matches under the deferred acceptance algorithm. However, these theoretical results are based on the over-simplifying assumption that all students share the same preference ranking for schools. In this work, we relax this assumption and allow students to have heterogeneous preference rankings. Under a game-theoretic model where student strategies form a Bayesian Nash equilibrium, we characterize scenarios where revealing the lottery number can either improve or worsen the matching outcome, measured by two metrics of match rate and social welfare. We further consider revealing partial information about the lottery, and demonstrate non-monotonic effects in the amount of information available to students. These results together illustrate complex tradeoffs induced by the lottery revealing policy. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.34074 |
| By: | Elizabeth Baldwin; Paul Klemperer; Edwin Lock |
| Abstract: | Arctic product-mix auctions allow budget-constrained bidders to express preferences over multiple substitute goods. We give the first strongly polynomial algorithm to find the competitive equilibria when the auctioneer has separable convex piecewise-linear costs. It combines a strongly polynomial reduction to the costless Arctic auction with an existing strongly polynomial algorithm for costless Arctic auctions. We also give a polynomial-time Turing reduction from costless Arctic auctions to linear Fisher markets, and a strongly polynomial many-to-one reduction to linear Arrow-Debreu exchange markets. If a good is sold in positive quantity in two competitive equilibria, its price is the same in both. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.36346 |
| By: | Vladimir Asriyan; William Fuchs; Caio Lorecchio |
| Abstract: | We study dynamic monopoly pricing with multiple buyers whose valuations are privately known and correlated, so that one buyer 's purchase reveals information about the valuations of others. Without seller commitment, these information spillovers alter future pricing incentives and feed back into current demand. We show that they generate strategic complementarities in buyers' purchase decisions, making demand non-monotone and giving rise to equilibrium multiplicity. Information spillovers can either strengthen or weaken the seller 's effective commitment power, implying that seller revenue, buyer surplus, and total welfare are generically non-monotonic in the strength of spillovers. We characterize when these spillovers encourage data investment and experimentation, as well as facilitate coordination that mitigates hold-up. |
| Keywords: | commitment, dynamic monopoly pricing, equilibrium multiplicity, information spillovers, strategic complementarities |
| JEL: | D42 D82 D83 |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:bge:wpaper:1598 |
| By: | Mark Whitmeyer |
| Abstract: | I show that the equivalence in finite social-choice environments of Bayesian incentive compatibility and dominant-strategy incentive compatibility holds universally if and only if every type-dependent difference in the valuation of prizes operates through a single scalar type index. Beyond binary domains this universal robustifiability is nongeneric. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.26223 |
| By: | Lei Huang (MIT Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA); Juanjuan Zhang (MIT Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA) |
| Abstract: | When supply incentives are driven by demand, the natural force of the market may suppress the provision of products that are valuable to some consumers, leading to market failure. This paper explores a solution. Focusing on content platforms, we design a recommendation mechanism that maximizes total user utility by strategically allocating demand to sustain valuable content production. Theoretically, we prove that the optimal recommendation mechanism considers not only consumption utility, as in standard recommender systems, but also creator sensitivity, which captures how easily a creator can be incentivized by demand, and creator contribution, which reflects a creator’s importance to users overall. Computationally, we develop PixSet, a novel data transformation framework that converts variable-length sets (e.g., numbers of creators of various types) into fixed-size tensors (e.g., density distribution over pixels in a type space), which simplifies estimation as a computer vision problem with 99.9% gain in computational efficiency. The proposed recommendation mechanism is validated by both an observational-data analysis and a field experiment on Tencent WeChat, one of the world's largest content platforms. This mechanism has since been deployed as the default recommendation system at WeChat, serving billions of users and tens of millions of creators each day. |
| Keywords: | mechanism design; recommender system; automation; creator economy |
| JEL: | D47 L11 C55 C61 |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:net:wpaper:2608 |
| By: | Juan Beccuti; Manvir Schneider |
| Abstract: | We study reward design for delegated representatives who acquire costly information and vote on a binary governance proposal. Effort improves both private information and delegated voting weight. We show that no payment rule can make sincere voting strictly optimal at every positive effort profile under a non-neutral prior, while fixed budgets limit accuracy in large symmetric committees. We then compare proportional sharing with a conditional rule that rewards only members of a sufficiently large winning coalition. Unlike proportional sharing, which supports sincere voting only through indifference, the conditional rule makes sincere voting strictly optimal at symmetric positive effort profiles. It supports sincere equilibria with the same effort as proportional sharing and, under suitable reward-cost conditions, with strictly higher effort and decision accuracy. Insincere equilibria may nevertheless coexist. |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.07959 |
| By: | Joshua S. Gans |
| Abstract: | A honeytoken, a decoy credential or record whose use reveals an intruder, produces defence intelligence only if an adversary sometimes treats it as genuine. The adversary can instead pay to fingerprint it. I model this problem as information design followed by receiver information acquisition. Without fingerprinting, a defender whose installed trap prevalence exceeds the adversary's participation boundary places the attacked pool exactly at that boundary: calibrated bait. That posterior also maximises the gross value of any fixed informative diagnostic with finitely many signal outcomes. For a perfect covert test, the resulting appearance design has a closed-form, prior-dependent characterisation: expensive testing preserves calibrated bait, intermediate-cost testing produces under-calibrated bait, and cheap testing yields pooling, protected segmentation or abstention. Free and costless adjustment of trap prevalence makes non-degenerate segmentation unnecessary, but a sufficiently large adjustment cost around a sufficiently high inherited composition can sustain it. Finally, along an exogenously declining fingerprinting-cost path, lower cost reduces trap activation without reducing genuine compromise within the under-calibrated regime. Evaluation against fresh attackers can therefore overstate the durability of reusable bait. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.26797 |
| By: | Julien Combe; Yves Le Yaouanq |
| Abstract: | Many markets are regulated for paternalistic reasons. We develop a mechanism-design framework to derive the optimal policy mix between price regulation and quantity controls. A budget-constrained planner allocates trade between privately informed buyers and sellers while disagreeing with their valuations. When the planner’s valuations preserve the ranking of agents, price instruments (e.g., sin taxes) are optimal. When the planner instead believes that a high willingness to trade indicates a bias, optimal regulation can restrict quantities or even prohibit transactions. De-biasing interventions offer two benefits beyond economic regulation: improving selection into markets and, for virtuous goods, raising the volume of trade. |
| Keywords: | paternalism, mechanism design, market regulation, rationing, sin taxes, nudges |
| JEL: | D82 D90 D47 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_13028 |
| By: | Wei He; Fei Li; Jiangtao Li; Hanqing Ye |
| Abstract: | A principal relies on information held by a biased agent in decision-making. Without a prior over the circumstances that may arise, she designs a delegation rule to minimize the worst-case regret. Optimal delegation combines a default action, a fixed gap above it, and a higher discretionary interval with random boundaries. This structure separates two margins: whether the decision departs from the default and how much discretion the agent receives conditional on doing so. The default and gap limit excessive adjustment when little adaptation is warranted, while the higher interval preserves flexibility when larger adjustments are needed. Randomizing the discretionary interval's floor and ceiling hedges the principal's exposure across potential worst-case states. This rule is optimal among all stochastic incentive-compatible mechanisms. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.35156 |
| By: | Tommaso Bondi (SC Johnson College of Business, Cornell University, Ithaca, NY, USA); Lijuan Luo (SC Johnson College of Business, Cornell University, Ithaca, NY, USA) |
| Abstract: | Online reviews are usually modeled as quality signals, but their text also tells readers which products suit them. We study this matching role in a dynamic model in which majority and minority consumers care about partly different product features. As matching improves, each product’s buyers become more alike, and its reviews say less about the features that matter only to consumers of the other type. The unique equilibrium therefore features partial matching, sustained by mismatched buyers whose reviews cover what matched buyers leave out. In the benchmark model, uniformly degrading what consumers see never raises equilibrium matching. Pooled AI summaries of the most frequently mentioned features leave minority readers no better informed than a page written only by fans. Descriptive evidence from 11.6 million Goodreads reviews shows that review text separates fit from quality and that readers who like and dislike a book write about different things. This paper suggests that platforms can serve minority readers better by building AI summaries within reader segments and by not letting majority endorsement decide which reviews are most visible. |
| Keywords: | online reviews; product fit; social learning; information design; AI summaries; platform design |
| JEL: | D82 D83 L15 L86 M31 |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:net:wpaper:2603 |
| By: | Maria Andraos; Mario Ghossoub |
| Abstract: | We consider an insurance market with hidden information, where the agent's type is private information and is drawn from an arbitrary type space. We discuss the notion of implementability of the collection of retention functions. Namely, how to select premium schedules so that the resulting menu of contracts is incentive compatible, or truthtelling. Specifically, for general type spaces, implementability is equivalent to cyclical monotonicity of the collection of retention functions. For compact interval type spaces, we show that submodularity is a sufficient condition for implementability, under suitable type ordering assumptions. Moreover, for any implementable collection of retention functions, we characterize the corresponding premium schedule. Finally, we apply our results to several standard classes of insurance contracts, for which the general implementability conditions admit simpler characterizations, and we provide several numerical illustrations. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.31959 |
| By: | Jie Gong; Jiayi Hou; Jin Li; Fei Pu; Xinjue Yao |
| Abstract: | We study gaming and adaptive incentive design in AI adoption. A large medical-device company required roughly 5, 000 employees to submit at least 200 queries per month to an internal AI assistant. First-time use increased significantly after the mandate, but usage patterns suggested gaming: query counts bunched at the threshold, and 31 percent of queries were repeated or off-task. The firm subsequently revised incentive design and lowered the target to 100. Using staggered implementation across branches, we estimate that the adjustment reduced query volume by 30 percent, with repeated or off-task queries accounting for about 90 percent of the decline. The estimated change in non-repeated, work-related queries was small and statistically insignificant. Among sales employees, monthly sales increased by 7 percent. The findings identify incentive adaptation as a consequential margin of technology adoption: recalibrating usage requirements can reduce gaming and improve employee performance. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.32859 |
| By: | Irene Aldridge |
| Abstract: | Market microstructure studies how trading rules turn orders into prices and allocations. Those rules have been rebuilt repeatedly: for floor traders, electronic limit order books and high-frequency trading, batch auctions and dark pools, blockchains run by automated market makers and block builders, and now AI agents that discover, pay for, and compete over resources. This survey traces that evolution through one question: can a market allocate scarce goods efficiently and fairly without participants revealing everything they know and want? Each technological shift moved the binding constraint of market design from trader rationality to speed, to control over transaction ordering, to the dimensionality of what participants can report. Impossibility results persist; only their cost moves. We review evidence on high-frequency trading, trading venues, automated market makers, extractable value and algorithmic collusion, and identify allocation as the missing layer of the agent-commerce protocol stack. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.33058 |
| By: | MohammadHossein Bateni; Zahra Hadizadeh; MohammadTaghi Hajiaghayi; Mahdi JafariRaviz; Shayan Taherijam |
| Abstract: | We study information aggregation in the networked learning model introduced by Kearns, Roth, and Ryu (SODA 2026). There is a fixed distribution over $d$ features and a common label. Agents learn in topological order on a directed acyclic graph. Each observes a subset of the features and its parents' predictions, fits a linear predictor to minimize mean squared error, and passes only its prediction forward. The global predictor is the best linear predictor using all features. Kearns, Roth, and Ryu show that the output agent's error approaches the global predictor's error along sufficiently deep paths with suitable feature coverage, while insufficient depth can prevent aggregation even in large networks. In contrast to their main focus on a given graph and feature allocation, we consider the limits of the model under two settings. In the adaptive designer setting, a designer chooses the graph, feature allocation, and output agent knowing the distribution. In the oblivious designer setting, the designer fixes all three before an adversary chooses the distribution. Each agent observes one feature and receives predictions from a limited number of parents. We call the aggregation exact when the output agent matches the global predictor exactly. For $d\ge3$, we show that no finite depth guarantees exact aggregation for every distribution with one parent per agent, even when the designer knows the distribution. In contrast, two parents per agent suffice for exact aggregation even in the oblivious designer setting. A fixed graph, feature allocation, and output agent achieve this for every distribution at depth $O(d\log d)$. Knowing the distribution reduces the depth to $O(d)$. Both constructions use $O(d^2)$ agents, with a very large constant for two parents. We show the bounds on the depth and number of agents are all optimal up to constant factors. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.35537 |
| By: | Jonathan Libgober |
| Abstract: | I introduce a robustness criterion for settings where players may disagree about the distribution over signals induced by endogenously chosen information. In the spirit of Hansen and Sargent (2008), an information choice is evaluated by its worst-case payoff over beliefs within an $\eta$-entropy ball around the signal distribution it induces. I apply this formulation to buyer-optimal learning in bilateral trade (Roesler and Szentes, 2017). If trade is always efficient, disagreement raises the price and twists the buyer's demand curve while preserving full trade. When trade may be inefficient, the same characterization holds conditional on trade with an endogenously amplified disagreement level. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.33057 |
| By: | Takashi Shimizu (Graduate School of Economics, Kobe University) |
| Abstract: | We study information transmission within organizations, focusing on how biased Subordinates should be combined to elicit truthful information. We assume that the directions of the Subordinates’ biases are common knowledge, whereas their magnitudes are privately known to each Subordinate. We show that a homogeneous composition of Subordinates is preferable to a heterogeneous one. The intuition is that, under a homogeneous composition, the effect of an individual false report is amplified by false reports from other Subordinates. Anticipating this amplification effect reduces each Subordinate’s incentive to misreport and thereby promotes truthful information transmission. |
| Keywords: | Cross-holdings: Organization; Information transmission; Cheap talk; Bias; Homogeneous mode; Heterogeneous mode |
| JEL: | D23 D82 |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:koe:wpaper:2614 |
| By: | Xiaoming Cai; Pieter Gautier |
| Abstract: | Search frictions normally raise the bar for sorting: both random and directed search require complementarities strictly stronger than the supermodularity that suffices in Becker's (1973) frictionless model. We introduce private information into this setting: firms post wages without observing worker productivity, while better workers have better outside options, creating a market for lemons (Akerlof 1970). We show that this information friction pushes sorting the other way: attracting high-productivity workers without attracting low-productivity ones requires a higher wage paired with a lower job-finding probability, so vacancies fill faster. This strict ranking of vacancy-filling rates sorts the market positively whenever output is complementary in worker and firm quality. Becker's condition therefore suffices once more, and private information makes positive sorting easier to sustain than complete information does. |
| Keywords: | competitive search, adverse selection, screening, sorting, positive assortative matching |
| JEL: | C78 D82 D83 J64 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_13031 |
| By: | Georgy Lukyanov; Mikhail Zolotarev |
| Abstract: | Public support for early adoption can affect what later users learn from observed choices. An adopter may have favourable private information, or may have received a rebate. We study a government that randomly assigns eligibility for a fixed rebate and chooses the program's coverage and reporting rule. We characterize when disclosing individual eligibility changes optimal coverage from zero to a positive rate under general convex program costs. This requires both a favourable marginal return to a disclosed program and a bound on the direct benefit available from a large opaque intervention. In the benchmark, disclosure allows the government to increase early adoption and welfare while leaving expected total adoption unchanged. We then allow imperfect compliance and private information for the late user. An eligibility label can be strictly informative without changing anyone's decision, in which case disclosure has no welfare value. The policy reversal survives when both extensions are present. The results identify when an eligibility record is a useful part of the design of an adoption program. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.31744 |
| By: | Georgy Lukyanov; Nikita Ogorodnikov |
| Abstract: | New information services begin without a record that teaches customers how to interpret them. We study a two-period monopoly selling standardized forecasts whose committed scoring technology combines noisy evidence with a persistent, initially unknown calibration. More evidence improves a forecast's current decision value but makes the source's calibration harder to learn. The first forecast is released publicly only after its immediate use expires, so it builds a common decoder for the next forecast. For an arbitrary stakes distribution, monopoly pricing uses the same static cutoff in both periods. Provider patience lowers initial evidence intensity; with identical technologies and a binary format menu, transparent conditions generate an endogenous low-evidence first forecast followed by a high-evidence second forecast. A constrained planner switches later because monopoly undercaptures the return to costly evidence. A calibration audit eliminates the accuracy--interpretability trade-off, but the provider may not adopt it even when adoption is socially valuable. The mechanism requires neither distorted reporting nor confirmation preferences: the strategic choice is the auditable evidence input to a mechanically generated score. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.31745 |
| By: | Steven Kivinen (University of Graz, Austria); Tatiana Mayskaya (International College of Economics and Finance; HSE University, Russia); Arina Nikandrova (University of London, UK) |
| Abstract: | A sender must disclose all available signals but commits to their order to persuade a receiver who pays to observe them sequentially and can stop at any time. Front loading favourable signals is generally suboptimal. With many weak signals, an asymptotically optimal policy uses the first signal to encode a recommendation based on the entire sample, then alternates favourable and unfavourable signals to postpone revelation of the sample composition and deter further learning. This policy makes the dynamic ordering problem asymptotically equivalent to static persuasion with costly verification. |
| Keywords: | information design, costly information acquisition, optimal stopping, primacy effect |
| JEL: | D82 D83 |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:grz:wpaper:2026-21 |
| By: | Xiaoming Cai (Peking University HSBC Business School); Pieter Gautier (Vrije Universiteit Amsterdam) |
| Abstract: | Search frictions normally raise the bar for sorting: both random and directed search require complementarities strictly stronger than the supermodularity that suffices in Becker's (1973) frictionless model. We introduce private information into this setting: firms post wages without observing worker productivity, while better workers have better outside options, creating a market for lemons (Akerlof 1970). We show that this information friction pushes sorting the other way: attracting high-productivity workers without attracting low-productivity ones requires a higher wage paired with a lower job-finding probability, so vacancies fill faster. This strict ranking of vacancy filling rates sorts the market positively whenever output is complementary in worker and firm quality. Becker's condition therefore suffices once more, and private information makes positive sorting easier to sustain than complete information does. |
| Keywords: | Competitive search, adverse selection, screening, sorting, positive assortative matching |
| Date: | 2026–10–05 |
| URL: | https://d.repec.org/n?u=RePEc:tin:wpaper:20260081 |
| By: | Yuki Shiomi; Nobuyuki Hanaki |
| Abstract: | We experimentally examine whether partial commitment to the message distribution can substitute for full commitment to the information structure in Bayesian persuasion. Theory predicts that when the players’ marginal incentives are aligned, an equilibrium with the same level of information transmission as under full commitment can be sustained even under partial commitment, whereas when marginal incentives are misaligned, no information can be credibly transmitted. Our central finding is that, even when marginal incentives are aligned, information transmission is substantially lower under partial commitment than under full commitment: partial commitment does not fully substitute for full commitment in practice. When marginal incentives are misaligned, information transmission declines further under partial commitment, as theory predicts. We also find that misaligned marginal incentives reduce information transmission even under full commitment, where the standard theory predicts no such effect. Our analysis of sender behavior shows that, in all of these cases, senders transmit less information than the theoretical benchmark implies, suggesting that sender undercommunication plays an important role in the lower information transmission we observe. |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:dpr:wpaper:1322 |
| By: | Marco Pariguana; Diether Beuermann |
| Abstract: | Choosing a school is one of the most important decisions parents make regarding their children's human capital, yet application constraints can make observed choices an imperfect measure of what parents value. We study preferences for school effectiveness and peer quality in the centralized secondary school market of Barbados, where admissions are based on a one-shot exam and parents face a binding cap on the number of schools they can list. Exploiting a policy reform that further tightened this cap, we show that parents respond by 'skipping the impossible': omitting the most selective schools from their applications, with little change in equilibrium assignments. We then estimate preferences for school effectiveness, measured by impacts on test scores and adult wages, and peer quality under alternative behavioral assumptions. Under the truth-telling assumption that applications reveal parents' most preferred schools, we find no evidence that parents value school effectiveness conditional on peer quality. In contrast, under market-stability assumptions that allow parents to omit desirable but seemingly unattainable schools, we find that parents value both school effectiveness and peer quality. The difference arises because the most selective schools are also the most effective. Thus, approaches that interpret omitted schools as less preferred than ranked ones can understate parental demand for school effectiveness. |
| Keywords: | School choice, Secondary education, Education policy |
| JEL: | I21 I24 I28 J24 |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:26230 |
| By: | Herbert Dawid; Ali Kashefi; Gerd Muehlheusser |
| Abstract: | Should platforms be held legally responsible for harm caused by products or services offered by third-party sellers? We address this question in a novel setting in which product safety (the likelihood of accidents) is determined by third-party sellers, while the consumer price is set by a monopolistic platform that pays sellers a commission. Relevant examples include platforms providing ride-hailing services (e.g. Uber and Lyft) or health care services (e.g. Teladoc). Sellers decide whether or not to become active on the platform, and consumers' willingness to pay for the platform good increases with the number of active sellers (platform externality). When an accident occurs, the harm is divided between the platform and the respective seller according to a liability rule set ex ante by a welfare-maximizing policymaker. Sellers' incentive to provide high product safety is driven by market demand, which in turn is determined by the platform's pricing scheme, balancing the trade-off between market revenue and expected liability costs. The platform may optimally set a price below the monopoly level to boost demand, thereby triggering active sellers to provide high product safety (market channel). The socially optimal liability rule is dichotomous: it either assigns no liability to the platform, or the maximum liability share for which the platform exploits the market channel to induce high product safety from the sellers. Holding the platform liable is socially desirable only when it induces lower consumer prices. |
| Keywords: | platform liability, consumer pricing, product safety, product liability |
| JEL: | K13 L13 L15 L86 D42 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_13033 |
| By: | Erica Chiang; Kenny Peng; Rebecca Lichtenstein; Brielle McDaniel; Kristen O'Neil; Deja Thomas; Lianna Wright; Jon Kleinberg; Eva Tardos; Nikhil Garg |
| Abstract: | Algorithmic recommendations can help participants navigate large matching markets. For example, recommendations for school and college choices may reduce information frictions and disparities in access to high-performing programs. At scale, however, recommenders in capacity-constrained settings can be self-defeating: if they steer too many users toward the same items, then even users who were originally predicted to have a high chance of matching to an item may not, due to increased competition. In this paper, we formalize this phenomenon of recommendation-induced congestion; motivated by the NYC high school match, we show that naive recommendations can cause sharp decreases in program acceptance rates, most affecting applicants with the fewest nearby options. Next, we propose and theoretically analyze a congestion-aware, bilevel optimize-and-simulate approach to allocate recommendations and improve match outcomes safely, in equilibrium. Finally, we deploy this approach in the 2025-26 admissions cycle of the NYC high school match, aiming to reduce disparities by highlighting personalized lists of nearby, high-performing programs where an applicant has a high predicted offer likelihood. In a randomized controlled trial, we find that 16.4% of treatment applicants ranked a recommended program, versus 10.5% of control applicants who ranked a program they would have been recommended (57% relative increase; $p$=0.011); 5.6% of treatment applicants matched to such a program, versus 3.3% of control applicants (71% relative increase; $p$=0.071); further, no treatment applicant was rejected from a recommended program. Our findings suggest that recommenders should be analyzed and designed as market-shaping interventions. |
| Date: | 2026–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2610.08275 |