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on Economic Design |
| By: | Martino Banchio; Andrzej Skrzypacz; Frank Yang |
| Abstract: | A seller wants to sell a good to a set of bidders using a credible mechanism. We show that when the seller has private information about her cost, it is impossible for a static mechanism to achieve the optimal revenue. In particular, even the optimal first-price auction is not credible. We show that the English auction can credibly implement the optimal mechanism, unlike the optimal Dutch auction. For symmetric mechanisms in which only winners pay, we also characterize all the static auctions that are credible: They are first-price auctions that depend only on the seller's cost ex post via a secret reserve, and may profitably pool bidders via a bid restriction. Our impossibility result highlights the role of public institutions and helps explain the use of dynamic mechanisms in informal auctions. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.21439 |
| By: | Dube, Devwrat |
| Abstract: | We study a single-server queue with fixed-length shifts $T > 1$ where service of unit length jobs is non-pre-emptive; residual time shorter than one job, namely fractional part of $T$, at boundaries is lost. Agents have constant private unit waiting costs. The efficient rule partitions agents into feasible shifts, orders shifts by the sum of members' costs, and orders agents within each shift by their costs. We show, by \citet{Holmstrom} and \citet{Suijs} type arguments, that only Vickrey-Clarke-Groves (VCG) transfers implement efficiency in dominant strategies. We then delineate when efficiency and DSIC implementation can be combined with budget balance (first-best mechanisms). If shifts are of unit-capacity ($1 2$ is non-integral (so each shift can host at least two agents but leaves residual slack), no first-best mechanism exists. The proof uses a the cubical-array lemma of \citet{Walker} adapted to our setting. |
| Keywords: | Queueing, Dominant Strategy Implementation, VCG, First-Best Mechanisms |
| JEL: | C72 D61 D63 D82 |
| Date: | 2025–10–12 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:126465 |
| By: | Bo Cowgill (Columbia Business School, Columbia University, New York, NY, USA); Zikai Xu (Department of Economics, Columbia University, New York, NY, USA) |
| Abstract: | This paper develops a mechanism design approach to network formation. A principal has a willingness-to-pay (WTP) for different network configurations while agents have preferences over their network positions. Our approach allows the principal to optimize for global properties of the network, while respecting IC/IR constraints of network participants. We focus on direct mechanisms but develop a broader family of mechanisms in which transfers are set by the allocation rule ("revenue equivalence"). We characterize optimal mechanisms under novel multidimensional regularity conditions and provide an ironing procedure for irregular distributions. These findings contribute to multidimensional mechanism design, with potential applications to network formation in social, economic, and organizational contexts. |
| Keywords: | mechanism design; virtual values; network formation |
| JEL: | D85 L14 D44 D82 D86 D2 M5 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:net:wpaper:2501 |
| By: | Yaron Azrieli (The Ohio State University); Ritesh Jain (University of Liverpool); Semin Kim (Yonsei University) |
| Abstract: | We study the design of voting mechanisms in a binary social choice environment where agents' cardinal valuations are independent but not necessarily identically distributed. The mechanism must be anonymous - the outcome is invariant to permutations of the reported values. We show that if there are two agents then expected welfare is always maximized by an ordinal majority rule, but with three or more agents there are environments in which cardinal mechanisms that take into account preference intensities outperform any ordinal mechanism. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:yon:wpaper:2025rwp-265 |
| By: | Smolin, Alex; Yamashita, Takuro |
| Abstract: | We study information design in games where players choose from a continuum of ac-tions and have continuously differentiable payoffs. We show that an information structure is optimal when the equilibrium it induces can also be implemented in a principal-agent contracting problem. Building on this result, we characterize optimal information struc-tures in symmetric linear-quadratic games. With common values, targeted disclosure is robustly optimal across all priors. With interdependent and normally distributed values, linear disclosure is uniquely optimal. We illustrate our findings with applications in venture capital, Bayesian polarization, and price competition. |
| Keywords: | Bayesian persuasion; information design; dual certification; first-order approach; linear-quadratic games; targeted disclosure; Gaussian coupling, linea; disclosure. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:130998 |
| By: | Weijie Zhong |
| Abstract: | We build a mechanism design framework where a platform designs GenAI models to screen users who obtain instrumental value from the generated conversation and privately differ in their preference for latency. We show that the revenue-optimal mechanism is simple: deploy a single aligned (user-optimal) model and use token cap as the only instrument to screen the user. The design decouples model training from pricing, is readily implemented with token metering, and mitigates misalignment pressures. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.09859 |
| By: | Agathe Pernoud; Frank Yang |
| Abstract: | A monopolist sells multiple goods to an uninformed buyer. The buyer chooses to learn any one-dimensional linear signal of their values for the goods, anticipating the seller's mechanism. The seller designs an optimal mechanism, anticipating the buyer's learning choice. In a generalized Gaussian environment, we show that every equilibrium has vertical learning where the buyer's posterior means are comonotonic, and every equilibrium is outcome-equivalent to nested bundling where the seller offers a menu of nested bundles. In equilibrium, the buyer learns more about a higher-tier good, resulting in a higher posterior variance on the log scale. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.16396 |
| By: | Itai Arieli; Yakov Babichenko; Atulya Jain; Rann Smorodinsky |
| Abstract: | We study games with incomplete information and characterize when a feasible outcome is Pareto efficient. We show that any outcome with excessive randomization over actions is inefficient. Generically, efficiency requires that the total number of actions taken across states be strictly less than the sum of the number of players and states. We then examine the efficiency of equilibrium outcomes in communication models. Generically, a cheap talk outcome is efficient only if it is pure. When the sender's payoff is state-independent, it is efficient if and only if the sender's most preferred action is chosen with certainty. In natural buyer-seller settings, Bayesian persuasion outcomes are inefficient across a wide range of priors and preferences. Finally, we show that our results apply to mechanism design problems with many players. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.12508 |
| By: | Bergemann, Dirk; Bonatti, Alessandro; Smolin, Alex |
| Abstract: | We develop an economic framework to analyze the optimal pricing and product design of Large Language Models (LLM). Our framework captures several key features of LLMs: variable operational costs of processing input and output tokens; the ability to customize models through fine-tuning; and high-dimensional user heterogeneity in terms of task requirements and error sensitivity. In our model, a monopolistic seller offers multiple versions of LLMs through a menu of products. The optimal pricing structure depends on whether token allocation across tasks is contractible and whether users face scale constraints. Users with similar aggregate value-scale characteristics choose similar levels of fine-tuning and token consumption. The optimal mechanism can be implemented through menus of two-part tariffs, with higher markups for more intensive users. Our results rationalize observed industry practices such as tiered pricing based on model customization and usage levels. |
| Keywords: | Large Language Models; Optimal Pricing; Menu Pricing; Fine-Tuning |
| JEL: | D47 D82 D83 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:130997 |
| By: | Jens Abildtrup; Géraldine Bocquého; Kene Boun My; Anne Stenger; Tuyen Tiet |
| Abstract: | We conduct a lab experiment to investigate the impact of voluntary and mandatory joint-bidding schemes on the performance of conservation auctions. Our results suggest that joint bidding increases auction performance compared to the singlebidding baseline. Within the voluntary joint-bidding conditions, a bonus payment incentive improves auction performance by encouraging the subjects to give low bids. However, voluntary joint bidding performs worse than mandatory joint bidding, even with the bonus incentive. Therefore, when implementing voluntary joint bids to ensure high acceptability from landowners compared to mandatory ones, policymakers should carefully consider performance issues. |
| Keywords: | Auction; Conservation; Mandatory; Joint bidding; Voluntary |
| JEL: | C57 C90 D70 Q50 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ulp:sbbeta:2025-40 |
| By: | Alejandro Francetich; Burkhard C. Schipper (Department of Economics, University of California Davis) |
| Abstract: | We consider a principal who wishes to screen an agent with \emph{discrete} types by offering a menu of \emph{discrete} quantities and \emph{discrete} transfers. We assume that the principal's valuation is discrete strictly concave and use a discrete first-order approach. We model the agent's cost types as non-integer, with integer types as a limit case. Our modeling of cost types allows us to replicate the typical constraint-simplification results and thus to emulate the well-treaded steps of screening under a continuum of contracts. We show that the solutions to the discrete F.O.C.s need not be unique \textit{even under discrete strict concavity}, but we also show that there cannot be more than two optimal contract quantities for each type, and that---if there are two---they must be adjacent. Moreover, we can only ensure weak monotonicity of the quantities \textit{even if virtual costs are strictly monotone}, unless we limit the ``degree of concavity'' of the principal's utility. Our discrete screening approach facilitates the use of rationalizability to solve the screening problem. We introduce a rationalizability notion featuring robustness with respect to an open set of beliefs over types called \textit{$\Delta$-O Rationalizability}, and show that the set of $\Delta$-O rationalizable menus coincides with the set of usual optimal contracts---possibly augmented to include irrelevant contracts. |
| Keywords: | Screening, discrete concave optimization, rationalizability, level-$k$ reasoning |
| JEL: | D82 |
| Date: | 2025–10–23 |
| URL: | https://d.repec.org/n?u=RePEc:cda:wpaper:375 |
| By: | H\'ector Hermida-Rivera |
| Abstract: | This note characterizes every qualified majority voting rule with a quota $q$ strictly greater than half of the voter set in environments with just two alternatives through anonymity, responsiveness, and $q$-neutrality. Crucially, the latter imposes independence of the labels of the alternatives only for all preference profiles in which some alternative is strictly top-ranked by at least $q$ voters. Thus, this note generalizes May's (1952, Theorem, p.~682) well-known axiomatic characterization of the simple majority voting rule to qualified majority voting rules with a quota $q$ strictly greater than half of the voter set. In doing so, it shows that these qualified majority voting rules are precisely distinguished by their "degree" of neutrality. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.19823 |
| By: | Ichihashi, Shota; Smolin, Alex |
| Abstract: | In markets where algorithmic data processing is increasingly prevalent, recom-mendation algorithms can substantially affect trade and welfare. We consider a setting in which an algorithm recommends a product based on its value to the buyer and its price. We characterize an algorithm that maximizes the buyer’s expected payoff and show that it strategically biases recommendations to induce lower prices. Revealing the buyer’s value to the seller leaves overall payoffs un-changed while leading to more dispersed prices and a more equitable distribution of surplus across buyer types. These results extend to all Pareto-optimal algorithms and to multiseller markets, with implications for AI assistants and e-commerce ranking systems. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:130999 |
| By: | Deniz Kattwinkel; Justus Preusser |
| Abstract: | This note applies tightness (Kattwinkel and Preusser (2025)) to the setting of Border and Sobel (1987, "Samurai Accountant: A Theory of Auditing and Plunder"). Border and Sobel characterize efficient mechanisms and argue that efficiency entails no loss of optimality. We characterize tight mechanisms and argue that tightness entails no loss of optimality. We show that tight mechanisms form a subset of efficient mechanisms. Therefore, tightness refines efficiency without loss of optimality. By characterizing tight mechanisms, one can replicate the insights from Border and Sobel (1987) and Chander and Wilde (1998). A novel insight is how and in which order the principal uses different instruments to provide incentives to different agent types. Further, we describe a procedure for constructing efficient mechanisms in a setting with a continuum of types. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.24673 |
| By: | Siyang Xiong |
| Abstract: | Focusing on stochastic finite-action mechanisms, we study implementation in undominated strategies and iteratively undominated strategies. We establish both possibility and impossibility results that resolve the open question in B\"orgers (1995). Contrary to the conventional understanding that positive results on Nash implementation need separability, quasilinearity, or infinite action sets, we provide -- to our knowledge -- the first positive result beyond those demanding assumptions. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.20790 |
| By: | Izgarshev, Mark; Lukyanov, Georgy |
| Abstract: | A benevolent advisor observes a project’s complexity and posts a pass–fail threshold before the agent chooses effort. The project suc-ceeds only if ability and effort together clear complexity. We com-pare two informational regimes. In the naive regime, the threshold is treated as non-informative; in the sophisticated regime, the threshold is a signal and the agent updates beliefs. We characterize equilibrium threshold policies and show that the optimal threshold rises with com-plexity under mild regularity. We then give primitives-based sufficient conditions that guarantee separating, pooling, or semi-separating out-comes. In a benchmark with uniform ability, exponential complexity, and power costs, we provide explicit parameter regions that partition the space by equilibrium type; a standard refinement eliminates most pooling. The results yield transparent comparative statics and welfare comparisons across regimes. |
| Keywords: | threshold tests; signaling; information design; monotone comparative statics; pooling vs. separation. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:131005 |
| By: | Alejandro Francetich; Burkhard Schipper (Department of Economics, University of California Davis) |
| Abstract: | We analyze a principal-agent procurement problem in which the principal (she) is unaware some of the marginal cost types of the agent (he). Communication arises naturally as some types of the agent may have an incentive to raise the principal's awareness (totally or partially) before a contract menu is offered. The resulting menu must not only reflect the principal's change in awareness, but also her learning about types from the agent's decision to raise her awareness in the first place. We capture this reasoning in a discrete concave model via a rationalizability procedure in which marginal beliefs over types are restricted to log-concavity, ``reverse'' Bayesianism, and mild assumptions of caution. We show that if the principal is ex ante only unaware of high-cost types, all of these types have an incentive raise her awareness of them---otherwise, they would not be served. With three types, the two lower-cost types that the principal is initially aware of also want to raise her awareness of the high-cost type: Their quantities suffer no additional distortions and they both earn an extra information rent. Intuitively, the presence of an even higher cost type makes the original two look better. With more than three types, we show that this intuition may break down for types of whom the principal is initially aware of so that raising the principal's awareness could cease to be profitable for those types. When the principal is ex ante only unaware of more efficient (low-cost) types, then \textit{no type} raises her awareness, leaving her none the wiser. |
| Keywords: | Screening, disclosure, unawareness, principal-agent model, rationalizability |
| JEL: | D83 |
| Date: | 2025–10–23 |
| URL: | https://d.repec.org/n?u=RePEc:cda:wpaper:374 |
| By: | Andrew Li; R. Ravi; Karan Singh; Zihong Yi; Weizhong Zhang |
| Abstract: | Motivated by the problem of selling large, proprietary data, we consider an information pricing problem proposed by Bergemann et al. that involves a decision-making buyer and a monopolistic seller. The seller has access to the underlying state of the world that determines the utility of the various actions the buyer may take. Since the buyer gains greater utility through better decisions resulting from more accurate assessments of the state, the seller can therefore promise the buyer supplemental information at a price. To contend with the fact that the seller may not be perfectly informed about the buyer's private preferences (or utility), we frame the problem of designing a data product as one where the seller designs a revenue-maximizing menu of statistical experiments. Prior work by Cai et al. showed that an optimal menu can be found in time polynomial in the state space, whereas we observe that the state space is naturally exponential in the dimension of the data. We propose an algorithm which, given only sampling access to the state space, provably generates a near-optimal menu with a number of samples independent of the state space. We then analyze a special case of high-dimensional Gaussian data, showing that (a) it suffices to consider scalar Gaussian experiments, (b) the optimal menu of such experiments can be found efficiently via a semidefinite program, and (c) full surplus extraction occurs if and only if a natural separation condition holds on the set of potential preferences of the buyer. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.15214 |