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on Microeconomics |
| By: | Laura Doval; Alex Smolin |
| Abstract: | We study mechanism design when a designer repeatedly uses a fixed mechanism to interact with strategic agents who learn from observing their allocations. We introduce a static framework, calibrated mechanism design, requiring mechanisms to remain incentive compatible given the information they reveal about an underlying state through repeated use. In single-agent settings, we prove implementable outcomes correspond to two-stage mechanisms: the designer discloses information about the state, then commits to a state-independent allocation rule. This yields a tractable procedure to characterize calibrated mechanisms, combining information design and mechanism design. In private values environments, full transparency is optimal and correlation-based surplus extraction fails. We provide a microfoundation by showing calibrated mechanisms characterize exactly what is implementable when an infinitely patient agent repeatedly interacts with the same mechanism. Dynamic mechanisms that condition on histories expand implementable outcomes only by weakening incentive compatibility and individual rationality--a distinction that vanishes in transferable utility settings. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.17858 |
| By: | Ernesto Rivera Mora (University of Colorado, Boulder); Philipp Strack (Yale University) |
| Abstract: | We study mechanism design for a sophisticated agent with non-expected utility (EU) preferences. We show that the revelation principle holds if and only if all types are EU maximizers: if at least one type is a non-EU maximizer, randomizing over dynamic mechanisms generates a strictly larger set of implementable allocations than using static mechanisms. Moreover, dynamic stochastic mechanisms can fully extract the private information of any type who doesn't have uniformly quasi-concave preferences without providing that type any rent. Full-surplus extraction is possible in a broad variety of non-EU environments, but impossible for types with concave preferences. |
| Date: | 2025–12–30 |
| URL: | https://d.repec.org/n?u=RePEc:cwl:cwldpp:2481 |
| By: | Hiroto Sato; Ryo Shirakawa |
| Abstract: | We develop a simple model of a designer who manages a learning structure. Agents have partial private information about a common-value good. The designer wishes to allocate the good to as many agents as possible without using monetary transfers. We formulate this environment as a mechanism design problem that nests social learning models and characterize an optimal mechanism under general distributions over private information. The optimal mechanism can be summarized by two parameters: one purely adjusts the allocation probability, while the other governs the amount of learning implicitly induced by allocation. Although the designer always prefers to allocate the good, managing incentives for learning leads the optimal mechanism to withhold allocation even when allocation is socially efficient. Our analysis brings the perspective of managing learning structures to market design and introduces a mechanism design approach to social learning. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.20001 |
| By: | Dirk Bergemann (Yale University); Marek Bojko (Yale University); Paul DŸtting (Google Research); Renato Paes Leme (Google Research); Haifeng Xu (University of Chicago and Google Research); Song Zuo (Google Research) |
| Abstract: | We study mechanism design in environments where agents have private preferences and private information about a common payoff-relevant state. In such settings with multi-dimensional types, standard mechanisms fail to implement efficient allocations. We address this limitation by proposing data-driven mechanisms that condition transfers on additional post-allocation information, modeled as an estimator of the payoff-relevant state. Our mechanisms extend the classic Vickrey-Clarke-Groves framework. We show they achieve exact implementation in posterior equilibrium when the state is fully revealed or utilities are affine in an unbiased estimator. With a consistent estimator, they achieve approximate implementation that converges to exact implementation as the estimator converges, and we provide bounds on the convergence rate. We demonstrate applications to digital advertising auctions and AI shopping assistants, where user engagement naturally reveals relevant information, and to procurement auctions with consumer spot markets, where additional information arises from a pricing game played by the same agents. |
| Date: | 2025–12–23 |
| URL: | https://d.repec.org/n?u=RePEc:cwl:cwldpp:2418r2 |
| By: | Muhammed Ceesay; Nicola Doni; Domenico Menicucci |
| Abstract: | This paper is about a procurement auction setting with two sellers in which before the auction seller i can make an investment which improves the ex ante probability distribution of his cost; seller j observes seller i's investment decision before bidding occurs. Under somewhat restrictive assumptions on the pre- and the post-investment cost distributions, Arozamena and Cantillon (2004) prove that in the first price auction seller i's investment induces seller j to bid more aggressively. This negative strategic effect contributes to AC's result that the investment incentive for seller i is stronger in the second price auction than in the first price auction. We prove that under weaker but economically significant assumptions, and discretely distributed costs, an investment by seller i may actually induce seller j to bid less aggressively in the first price auction (i.e., the strategic effect may be positive), and the investment incentive may be stronger in the latter auction. Moreover, in some cases the buyer prefers the first price auction precisely because it provides a stronger investment incentive, even though the second price auction is preferable when no investment is possible. We prove that the two auctions are not equivalent in a setting in which each seller has the option to invest and the sellers are ex ante symmetric, and that the second price auction gives a stronger investment incentive to the initially stronger seller than to the other seller (this increases asymmetries), but such result does not necessarily hold in the first price auction. |
| Keywords: | Procurement Auctions, First-Price Auction, Second-Price Auction, Pre-Auction Investment, Strategic Effect, Auction Ranking. |
| JEL: | D44 D82 L15 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:frz:wpaper:wp2026_01.rdf |
| By: | Marina Halac (Yale University); Elliot Lipnowski (Columbia University); Daniel Rappoport (University of Chicago) |
| Abstract: | We study the design of a contest in which a designer uses performance-contingent rankings and information disclosure to motivate an agent to exert effort. The agent's ability is unknown, and the designer's objective is to maximize the agent's expected effort. We show that the optimal ranking is a simple "pass-fail" rule, and the optimal information policy provides the agent with the minimum information necessary to keep them motivated. The results have implications for the design of workplace evaluations, academic grading, and other competitive environments where relative performance is used to incentivize effort. |
| Date: | 2025–12–15 |
| URL: | https://d.repec.org/n?u=RePEc:cwl:cwldpp:2480 |
| By: | Jussi Keppo; Yingkai Li |
| Abstract: | This paper studies optimal contract design in private market investing, focusing on internal decision making in venture capital and private equity firms. A principal relies on an agent who privately exerts costly due diligence effort and then recommends whether to invest. Outcomes are observable ex post even when an opportunity is declined, allowing compensation to reward both successful investments and prudent decisions to pass. We characterize profit maximizing contracts that induce information acquisition and truthful reporting. We show that three tier contracts are sufficient, with payments contingent on the agent's recommendation and the realized return. In symmetric environments satisfying the monotone likelihood ratio property, the optimal contract further simplifies to a threshold contract that pays only when the recommendation is aligned with an extreme realized return. These results provide guidance for performance based compensation that promotes diligent screening while limiting excessive risk taking. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.19405 |
| By: | Hoover, D. |
| Abstract: | This paper explores the profitability and impact of opaque selling in a monopolist market with endogenous product characteristics. Opaque selling is a strategy where a firm sells goods through a lottery mechanism that randomly rewards consumers with a product that is revealed after purchase. Using a standard two-good Hotelling model with endogenous product locations, I compare market equilibria for a monopolist under traditional selling and opaque selling. I find that opaque selling always earns the firm a higher profit when product locations are endogenous. Additionally, it generally induces the firm to select more extreme product varieties. Using an extension to the Salop circular city model, I also show that opaque selling results in the firm introducing fewer product varieties. In terms of welfare, opaque selling unambiguously increases producer surplus and reduces consumer surplus. Although consumption of the lottery good is welfare inefficient, opaque selling can potentially increase welfare by inducing the firm to serve more consumers than it would under traditional selling. These results suggest that opaque selling may be a more viable long-term strategy when firms are capable of adjusting their product mix. |
| Keywords: | Opaque Selling, Lottery Goods, Endogenous Products, Product Differentiation |
| JEL: | D42 L11 L12 |
| Date: | 2026–01–09 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2601 |
| By: | Dirk Bergemann (Yale University); Tibor Heumann (Pontificia Universidad Cat—lica de Chile); Stephen Morris (Massachusetts Institute of Technology) |
| Abstract: | How should a buyer design procurement mechanisms when suppliers' costs are unknown, and the buyer does not have a prior belief? We demonstrate that notably simple mechanisms Ñ those that share a constant fraction of the buyer utility with the seller Ñ allow the buyer to realize a guaranteed positive fraction of the efficient social surplus across all possible costs. Moreover, a judicious choice of the share based on the known demand maximizes the surplus ratio guarantee that can be attained across all possible (arbitrarily complex and non-linear) mechanisms and cost functions. Results apply to related nonlinear pricing and optimal regulation problems. |
| Date: | 2025–12–08 |
| URL: | https://d.repec.org/n?u=RePEc:cwl:cwldpp:2479 |
| By: | Dinko Dimitrov; Dipjyoti Majumdar |
| Abstract: | We study the implementability of stable matchings in a two-sided market model with one-sided incomplete information. Firms' types are publicly known, whereas workers' types are private information. A mechanism generates a matching and additional announcements to the firms at each report profile of workers' types. When agents' preferences are increasing in the types of their matched partner, we show that the assortative matching mechanism which publicly announces the entire set of reported types is incentive compatible. Furthermore, any mechanism that limits information disclosure to firms' lower contour sets of reported types remains incentive compatible. However, when information is incomplete on both sides of the market, assortative matching is no longer implementable. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.18764 |
| By: | Jawwad Noor; Fernando Payró Chew |
| Abstract: | We study a dynamic predator–prey game in which a predator can conceal its movement under naturally occurring environmental noise. In the safe state, forest noise is i.i.d., whereas in the dangerous state the predator contributes additional noise as it approaches the prey. The prey updates her beliefs about danger from the realized noise sequence and chooses whether to remain vigilant. We characterize equilibrium patterns of noise generated in the forest and show that a marker for deception is a hot-hand effect, whereby streaks persist with increasing probability. |
| Keywords: | belief biases, deception, endogenous information, optimal stopping |
| JEL: | D01 D9 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:bge:wpaper:1544 |
| By: | Sarah Auster; Yeon-Koo Che |
| Abstract: | This paper revisits the classic Pandora's box problem, studying a decision-maker (DM) who seeks to minimize her maximal ex-post regret. The DM decides how many options to explore and in what order, before choosing one or taking an outside option. We characterize the regret-minimizing search rule and show that the likelihood of opting out often increases as more options become available for exploration. We show that this ``choice overload" is driven by the DM's fear of ``selection error" -- the regret from searching the wrong options -- suggesting that steering choice via recommendations or cost heterogeneity can mitigate regret and encourage search. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.21192 |
| By: | Pascal Toquebeuf (GAEL - Laboratoire d'Economie Appliquée de Grenoble - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes) |
| Abstract: | This paper analyzes a dynamic adverse selection market where buyers hold ambiguous beliefs about seller quality, modeled using neo-additive Choquet capacities and updated via optimistic, pessimistic, and Generalized Bayesian rules. First, we show that the choice of updating heuristic has a direct and systematic effect on the severity of adverse selection. While the optimistic and pessimistic rules invariably mitigate or amplify the problem, respectively, the Generalized Bayesian rule's impact is conditional, its trajectory toward collapse, efficiency, or a stable partial market depending on a persistent 'tug-of-war' between the buyer's static ambiguity attitude and the evolving probabilistic evidence. Our second main finding is that these immediate effects compound over time, leading to fundamentally different market trajectories. The pessimistic rule can drive the market to complete collapse, the optimistic rule can foster full participation, and the Generalized Bayesian path depends on the interplay between the buyer's attitude and the evolving evidence. We further analyze how baseline ambiguity and ambiguity aversion modulate these dynamics, uncovering a complex role for ambiguity in shaping the rate of market evolution. |
| Keywords: | Adverse selection, Neo-additive, Updating, Pessimism, Optimism, Ambiguity |
| Date: | 2025–12–03 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05407714 |
| By: | Hanyu Li; Xiaotie Deng |
| Abstract: | Classic no-trade theorems attribute trade to heterogeneous beliefs. We re-examine this conclusion for AI agents, asking if trade can arise from computational limitations, under common beliefs. We model agents' bounded computational rationality within an unfolding game framework, where computational power determines the complexity of its strategy. Our central finding inverts the classic paradigm: a stable no-trade outcome (Nash equilibrium) is reached only when "almost rational" agents have slightly different computational power. Paradoxically, when agents possess identical power, they may fail to converge to equilibrium, resulting in persistent strategic adjustments that constitute a form of trade. This instability is exacerbated if agents can strategically under-utilize their computational resources, which eliminates any chance of equilibrium in Matching Pennies scenarios. Our results suggest that the inherent computational limitations of AI agents can lead to situations where equilibrium is not reached, creating a more lively and unpredictable trade environment than traditional models would predict. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.17952 |
| By: | Keisuke HATTORI; Takeshi YOSHIKAWA |
| Abstract: | We analyze a two-stage duopoly where rivals first make non-cooperative demand-expanding investments yielding non-excludable benefits and then compete in product markets. Two efficiency paradoxes emerge endogenously. First, when production technologies are identical, firms with less efficient investment technology earn higher profits. Second, firms disadvantaged in both production and investment can outperform superior rivals. The mechanism is that market-expanding investments benefit all firms while costs fall disproportionately on efficient investors, enabling inefficient firms to free-ride. These paradoxes persist across product differentiation, simultaneous timing, and alternative aggregation technologies. Subsidies intended to remedy market failures paradoxically exacerbate efficiency reversals. While efficiency heterogeneity enhances short-run welfare through complementary effects, it may undermine long-run market selection, potentially causing inefficient monopolization. Our framework applies to brand advertising, platform development, standard-setting, and industry reputation, revealing fundamental tensions between static welfare gains and dynamic efficiency, with implications for competition policy and strategic management in coopetitive markets. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:25126 |
| By: | Francesca Bastianello; Alex Imas |
| Abstract: | Why do people sometimes overreact to new information and other times underreact? We develop a model in which the strength of a signal—how much one should update their beliefs with new information—depends on multiple features of the information environment. Limited attention to these features leads to misperceptions of signal strength: people approach a problem with an experience-based prior, which they adjust only partially based on how much attention they pay to different features. This mechanism explains a wide range of belief-updating patterns. Insensitivity to a single feature generates underreaction to strong and overreaction to weak signals, and more neglected features amplify this. Insensitivity to multiple features can instead break that pattern: insensitivity to one feature can generate excess sensitivity with respect to another, leading to overreaction to both weak and strong signals. A series of experiments provides support for the model and its underlying mechanism. |
| JEL: | D01 D83 D9 D91 G02 G4 G41 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34638 |
| By: | Marcus Pivato (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, UP1 - Université Paris 1 Panthéon-Sorbonne) |
| Abstract: | In recent work, the author has developed a general category-theoretic framework for decision theory. This paper applies this to the category of orthomodular lattices. Every Boolean algebra is an orthomodular lattice, so this yields a new ("syntactic") model of decision-making with classical uncertainty. The lattice of closed subspaces of a Hilbert space is also an orthomodular lattice, so this also yields a new model of decision-making with quantum uncertainty. |
| Keywords: | syntactic decision theory, Boolean algebra, quantum uncertainty |
| Date: | 2025–12–11 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05398789 |