Joint work with S. Galperti.
American Economic Association P&P, 2023, Vol 113
Abstract: How does protecting the privacy of consumers affect the value of their personal data? We model an intermediary that uses consumers' data to influence the price set by a seller. When privacy is protected, consumers choose whether to disclose their data to the intermediary. When privacy is not protected, the intermediary can access consumers' data without their consent. We illustrate that protecting consumers' privacy has complex effects. It can increase the value of some consumers' data while decreasing that of others. Additionally, it can have redistributive effects, by benefiting some consumers at the expense of others. Furthermore, it can increase average prices and reduce trade.
Joint work with S. Galperti and A. Levkun.
Review of Economic Studies, 2023, Vol 90-5
Abstract: Many e-commerce platforms use buyers' personal data to intermediate their transactions with sellers. How much value do such intermediaries derive from the data record of each single individual? We characterize this value and find that one of its key components is a novel externality between records, which arises when the intermediary pools some records to withhold the information they contain. Ignoring this can significantly bias the evaluations of data records. Our analysis has several implications about compensating individuals for the use of their data, guiding companies' investments in data acquisition, and more broadly studying the demand side of data markets. Our method combines modern information design with classic duality theory and applies to a large class of principal-agent problems.
Abstract: We study the role of commitment in communication and its interactions with rules, which determine whether information is verifiable. Our framework nests models of cheap talk, information disclosure, and Bayesian persuasion. It predicts that commitment has opposite effects on information transmission under the two alternative rules. We leverage these contrasting forces to experimentally establish that subjects react to commitment in line with the main qualitative implications of the theory. Quantitatively, not all subjects behave as predicted. We show that a form of commitment blindness leads some senders to over communicate when information is verifiable and under communicate when it is not. This generates an unpredicted gap in information transmission across the two rules, suggesting a novel role for verifiable information in practice.
Joint work with Sevgi Yuksel.
Econometrica, 2022, Vol 90-1
Abstract: We study the competitive provision and endogenous acquisition of political information. Our main result identifies a natural equilibrium channel through which a more competitive market decreases the efficiency of policy outcomes. A critical insight we put forward is that competition among information providers leads to informational specialization: firms provide relatively less information on issues that are of common interest and relatively more information on issues on which agents' preferences are heterogeneous. This enables agents to acquire information about different aspects of the policy, specifically, those that are particularly important to them. This leads to an increase in social disagreement, which has negative welfare implications. We establish that, in large enough societies, competition makes every agent worse off by decreasing the utility that she derives from the policy outcome. Furthermore, we show that this decline cannot be compensated by the decrease in prices resulting from competition.
Abstract: Information provision in games influences behavior by affecting agents' beliefs about the state, as well as their higher-order beliefs. We first characterize the extent to which a designer can manipulate agents' beliefs by disclosing information. We then describe the structure of optimal belief distributions, including a concave-envelope representation that subsumes the single-agent result of Kamenica and Gentzkow (2011). This result holds under various solution concepts and outcome selection rules. Finally, we use our approach to compute an optimal information structure in an investment game under adversarial equilibrium selection.
Joint work with Simone Galperti.Revise & Resubmit at Theoretical Economics
Abstract: We study equilibrium behavior in incomplete-information games under two information constraints: seeds and spillovers. The former restricts which agents can initially receive information. The latter specifies how this information spills over to other agents. Our main result characterizes the equilibrium outcomes under these constraints, without making additional assumptions about the agents' initial information. This involves deriving a “revelation-principle” result for settings in which a mediator cannot communicate directly or privately with the agents. Our model identifies which spillovers are more restrictive and which seeds are more influential. Moreover, it generates predictions that hold robustly under a general class of spillover processes, which includes strategic communication. We apply our results to a problem of optimal organization design.
Abstract: Consumers supply a crucial input for the modern economy: their personal data. Yet, they often have limited control over who uses it and are imperfectly compensated in return. This status quo can lead to inefficiencies. Could a competitive market for personal data do better? We study a stylized competitive economy where consumers own their data and can sell it to a platform. The platform then uses this data to interact the corresponding consumers with a third-party merchant, from whom they can buy a product. We find that, despite its competitive nature, this economy is inefficient. The market failure stems from consumers exerting an externality on each other when selling their data, which is enabled by how the platform optimally uses this data. We propose two solutions to this inefficiency. The first one introduces a "data union," which manages consumers' data on their behalf and compensates them accordingly. The second one envisions trading in markets that determine not only who gets the data but also how this data is used.
Joint work with Sevgi Yuksel.
Abstract: We study a dynamic learning model in which heterogeneously connected Bayesian players choose between two activities: learning from one's own experience (work) or learning from the experience of others (search). Players who work produce an inflow of information which is local and dispersed around the society. Players who search, instead, aggregate the information produced by others and facilitate its diffusion, thereby transforming what inherently is a private good into information that everyone can access more easily. The structure of social connections affects the interaction between equilibrium information production and its social diffusion in ways that are complex and subtle. We show that increasing the connectivity of the society can lead to a strict decrease in the quality of social information. We link these inefficiencies to frictions in peer-to-peer communications. Moreover, we find that the socially optimal allocation of learning activities can differ dramatically from the equilibrium one. Under certain conditions, the planner would flip the equilibrium allocation, forcing highly connected players to work, and moderately connected ones to search. We conclude with an application that studies how resilient a society is to external manipulation of public opinion through changes in the meeting technology.
Download: Old Draft. Currently being revised: new draft available upon request