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on Microeconomics |
| By: | Navarra, Federico; Pino, Flavio; Sandrini, Luca |
| Abstract: | We study a hybrid marketplace where a vertically integrated platform competes with a seller in a horizontally differentiated downstream market. The platform has a data advantage and can price discriminate consumers, whereas the seller cannot. Our analysis shows that, by properly setting the per-unit transaction fee, the platform can always avoid head-to-head competition with the seller, regardless of the level of horizontal differentiation. Mandating data-sharing, which allows the seller to also price discriminate, does not seem to solve this problem and, in fact, aggravates it further, generally benefiting the platform. The seller is better off only if it is less efficient than the platform, whereas consumers are worse off. We propose that preventing the platform from adjusting the fee after the data-sharing mandate is not enough to reinstate competition in the downstream market. We then show that banning the hybrid business model and forbidding the use of data for price discrimination increase consumer surplus, even if the seller becomes a monopolist. In other words, we propose that the harm to competition comes from the platform's business model rather than from its information advantage. |
| Keywords: | hybrid platforms, data-sharing, vertical integration, price discrimination |
| JEL: | D42 L12 L41 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:zewdip:300680 |
| By: | Pietro Dall'Ara |
| Abstract: | I study the persuasion of a receiver who accesses information only if she exerts costly attention effort. The sender designs an experiment to persuade the receiver to take a specific action. The experiment also affects the receiver's attention effort, that is, the probability that she updates her beliefs. As a result, persuasion has two margins: extensive (effort) and intensive (action). The receiver's utility exhibits a supermodularity property in information and effort. By leveraging this property, I prove a general equivalence between experiments and persuasion mechanisms \`a la Kolotilin et al. (2017). Censoring high states is an optimal strategy for the sender in applications. |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2408.01250 |
| By: | Ollar, Mariann; Penta, Antonio |
| Abstract: | We study a framework for robust mechanism design that can accommodate various degrees of robustness with respect to agents’ beliefs, and which includes both the belief-free and Bayesian settings as special cases. For general belief restrictions, we characterize the set of incentive compatible direct mechanisms in general environments with interdependent values. The necessary conditions that we identify, based on a first-order approach, provide a unified view of several known results, as well as novel ones, including a robust version of the revenue equivalence theorem that holds under a notion of generalized independence that also applies to non-Bayesian settings. Our main characterizations informthe design of belief-based terms, in pursuit of various objectives in mechanism design, including attaining incentive compatibility in environments that violate standard single-crossing and monotonicity conditions. We discuss several implications of these results. For instance, we show that, under weak conditions on the belief restrictions, any allocation rule can be implemented, but full rent extraction need not follow. Information rents are generally possible, and they decrease monotonically as the robustness requirements are weakened. |
| Keywords: | Moment Conditions; Robust Mechanism Design; Incentive Compatibility; Interdependent Values; Belief Restrictions |
| JEL: | D62 D82 D83 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:129650 |
| By: | Deniz Kattwinkel; Alexander Winter |
| Abstract: | A group of privately informed agents chooses between two alternatives. How should the decision rule be designed if agents are known to be biased in favor of one of the options? We address this question by considering the Condorcet Jury Setting as a mechanism design problem. Applications include the optimal decision mechanisms for boards of directors, political committees, and trial juries. While we allow for any kind of mechanism, the optimal mechanism is a voting mechanism. In the terminology of the trial jury example: When jurors (agents) are more eager to convict than the lawmaker (principal), then the defendant should be convicted if and only if neither too many nor too few jurors vote to convict. This kind of mechanism accords with a judicial procedure from ancient Jewish law. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.07293 |
| By: | Gorkem Celik; Roland Strausz |
| Abstract: | We consider a monopolistic certifier selling certification services to a partially privately informed seller. The certifier can enable the seller to disclose her private information publicly, as well as gather additional market information about the good's quality publicly. We show that the certifier's optimal contract exhibits maximal disclosure but non-maximal information-gathering. Thus, optimal contracts eliminate private information but not market uncertainty; even though the latter would be costless, it is suboptimal as it requires excessive information rents to the seller. Thus, market inefficiencies remain due to market uncertainty but not due to private information. |
| Keywords: | certification, disclosure, information gathering, optimal information revelation, private information |
| JEL: | D82 |
| Date: | 2024–08–09 |
| URL: | https://d.repec.org/n?u=RePEc:bdp:dpaper:0045 |
| By: | Bo Chen; Marco Serena; Zijia Wang |
| Abstract: | We study all-pay auctions with private and affiliated binary values. To increase revenue (i.e., expected aggregate bid), the auction organizer can commit ex ante to fully disclosing or concealing bidders’ valuations. We find that full disclosure, as opposed to full concealment, always increases bidders’ expected payoffs. If affiliation in bidders’ valuations is low, full disclosure lowers ex ante expected revenue. If affiliation is high: 1) with two bidders, full disclosure lowers expected revenue, and 2) with many bidders, it tends to increase expected revenue. When the low valuation is zero, the auction becomes one with stochastic but affiliated participation, and information disclosure affects neither bidders’ payoffs nor the expected revenue. |
| Keywords: | All-pay auction, Affiliation, Stochastic participation, Disclosure policies |
| JEL: | C72 D44 D82 |
| URL: | https://d.repec.org/n?u=RePEc:mpi:wpaper:tax-mpg-rps-2023-05 |
| By: | Hershdeep Chopra |
| Abstract: | This paper examines an adverse selection environment where a sender with private information (high or low ability) tries to convince a receiver of their high ability. Without commitment or costly signaling, market failure can occur. Certification intermediaries reduce these frictions by enabling signaling through hard information. This paper focuses on a monopolistic certifier and its impact on equilibrium welfare and certificate design. Key findings show that the certifier often provides minimal information, pooling senders of varying abilities and leaving low rents for high-type senders, which typically disadvantages the receiver. However, when precise information is demanded, the certifier screens the sender perfectly, benefiting the receiver. Thus, the monopolistic intermediary has an ambiguous effect on market efficiency. The results emphasize the importance of high certification standards, which drive low-ability senders out of the market. Conditions for such equilibria are characterized, showing how simple threshold strategies by the receiver induce first-best outcomes. Additionally, the relationship between the characteristics of offered certificates and welfare is identified. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.19814 |
| By: | Peiran Xiao |
| Abstract: | I study the optimal design of performance or product ratings to motivate agents' performance or investment in product quality. The principal designs a rating that maps their quality (performance) to possibly stochastic scores. Agents have private information about their abilities (cost of effort/quality) and choose their quality. The market observes the scores and offers a wage equal to the agent's expected quality [resp. ability]. I first show that an incentive-compatible interim wage function can be induced by a rating (i.e., feasible) if and only if it is a mean-preserving spread of quality [resp. ability]. Thus, I reduce the principal's rating design problem to the design of a feasible interim wage. When restricted to deterministic ratings, the optimal rating design is equivalent to the optimal delegation with participation constraints (Amador and Bagwell, 2022). Using optimal control theory, I provide necessary and sufficient conditions under which lower censorship, and particularly a simple pass/fail test, are optimal within deterministic ratings. In particular, when the principal elicits maximal effort (quality), lower censorship [resp. pass/fail] is optimal if the density is unimodal [resp. increasing]. I also solve for the optimal deterministic ratings beyond lower censorship for general distributions and preferences. For general ratings, I provide sufficient conditions under which lower censorship remains optimal. In the effort-maximizing case, a pass/fail test remains optimal if the density is increasing. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.10525 |
| By: | Olivier, Jacques (HEC Paris) |
| Abstract: | I analyze welfare in a model where information acquisition is endogenous, information has real effects, and agents are rational. Hedgers derive a private benefit from holding the asset. Information improves welfare if real efficiency gains exceed cost of acquiring information and foregone gains from trade. I show three new results. Hedgers and speculators have different incentives to acquire information. Gains from trade are lower when hedgers acquire information than when speculators do. Agents may produce less information than would be socially optimal, in which case a contract whereby a firm pays a designated market-maker to lower her spread increases welfare. |
| Keywords: | Welfare; information; hedgers; speculators; feedback; regulation; designated market-makers |
| JEL: | D61 D82 G12 G14 |
| Date: | 2023–01–31 |
| URL: | https://d.repec.org/n?u=RePEc:ebg:heccah:1469 |
| By: | Deepal Basak; Joyee Deb; Aditya Kuvalekar |
| Abstract: | We study a canonical collective action game with incomplete information. Individuals attempt to coordinate to achieve a shared goal, while also facing a temptation to free-ride. Consuming more similar information about the fundamentals can help them coordinate, but it can also exacerbate free-riding. Our main result shows that more similar information facilitates (impedes) achieving a common goal when achieving the goal is sufficiently challenging (easy). We apply this insight to show why insufficiently powerful authoritarian governments may face larger protests when attempting to restrict press freedom, and why informational diversity in committees is beneficial when each vote carries more weight. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.14773 |
| By: | Angelo Petralia |
| Abstract: | We investigate the choice behavior of a decision maker (DM) who harms herself, by maximizing some distortion of her true preference, in which the first $i$ alternatives are moved to the bottom, in a reversed order. The deterministic declination of our pattern has no empirical power, but it allows to define a degree of self-punishment, which measures the extent of the denial of pleasure adopted by the DM in her decision. We analyze irrational choices that display the lowest degree of self-punishment, and a characterization of them is provided. Moreover, we characterize the choice behavior that exhibits the highest degree of self-punishment, and we show that it comprises almost all choices. We also characterize stochastic self-punishment, which collects all the Random Utility Models (RUMs) whose support is restricted to the harmful distortions of some preference. Full identification of the DM's preference and randomization over its harmful distortions is allowed if each alternative is selected from the ground set with probability greater than zero. Finally, the degree of self-punishment of harmful stochastic choices is characterized. |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2408.01317 |
| By: | Aniruddha Ghosh |
| Abstract: | We present novel monotone comparative statics results for steady state behavior in a dynamic optimization environment with misspecified Bayesian learning. We consider a generalized framework, based on Esponda and Pouzo (2021), wherein a Bayesian learner facing a dynamic optimization problem has a prior on a set of parameterized transition probability functions (models) but is misspecified in the sense that the true process is not within this set. In the steady state, the learner infers the model that best-fits the data generated by their actions, and in turn, their actions are optimally chosen given their inferred model. We characterize conditions on the primitives of the environment, and in particular, over the set of models under which the steady state distribution over states and actions and inferred models exhibit monotonic behavior. Further, we offer a new theorem on the existence of a steady state on the basis of a monotonicity argument. Lastly, we provide an upper bound on the cost of misspecification, again in terms of the primitives of the environment. We demonstrate the utility of our results for several environments of general interest, including forecasting models, dynamic effort-task, and optimal consumption-savings problems. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.17037 |