A signal is privacy‐preserving with respect to a collection of privacy sets if the posterior probability assigned to every privacy set remains unchanged conditional on any signal realization. We characterize the privacy‐preserving signals for arbitrary state space and arbitrary privacy sets. A signal is privacy‐preserving if and only if it is a garbling of a reordered quantile signal. Furthermore, distributions of posterior means induced by privacy‐preserving signals are exactly mean‐preserving contractions of that induced by the quantile signal. We discuss the economic implications of our characterization for statistical discrimination, the revelation of sensitive information in auctions and price discrimination.
A monotone function interval is the set of monotone functions that lie pointwise between two fixed monotone functions. We characterize the set of extreme points of monotone function intervals and apply this to a number of economic settings. First, we leverage the main result to characterize the set of distributions of posterior quantiles that can be induced by a signal, with applications to political economy, Bayesian persuasion, and the psychology of judgment. Second, we combine our characterization with properties of convex optimization problems to unify and generalize seminal results in the literature on security design under adverse selection and moral hazard.
A signal is privacy-preserving with respect to a collection of privacy sets, if the posterior probability assigned to every privacy set remains unchanged conditional on any signal realization. We characterize the privacy-preserving signals for arbitrary state space and arbitrary privacy sets. A signal is privacy-preserving if and only if it is a garbling of a reordered quantile signal. These signals are equivalent to couplings, which in turn lead to a characterization of optimal privacy-preserving signals for a decision-maker. We demonstrate the applications of this characterization in the contexts of algorithmic fairness, price discrimination, and information design.
We characterize the extreme points of first-order stochastic dominance (FOSD) intervals and show how these intervals are at the heart of many topics in economics. Using knowledge of these extreme points, we characterize the distributions of posterior quantiles under a given prior, leading to an analogue of a classical result regarding the distribution of posterior means. We apply this analogue to various economic subjects, including the psychology of judgement, political economy, and Bayesian persuasion. In addition, FOSD intervals provide a common structure to security design. We use the extreme points to unify and generalize seminal results in that literature when either adverse selection or moral hazard pertains.
This paper examines the welfare implications of third-party informational intermediation. A seller sets the price of a product that is sold through an informational intermediary. The intermediary can disclose information about the product to consumers and earns a fixed percentage of sales revenue in each period. The intermediary's market base grows at a rate that increases with past consumer surplus. We characterize the stationary equilibria and the set of subgame perfect equilibrium payoffs. When market feedback (i.e., the extent to which past consumer surplus affects future market bases) increases, welfare may decrease in the Pareto sense.
We assess the capacity of gerrymandering to undermine the will of the people in a representative democracy. Citizens have political positions represented on a spectrum, and electoral maps separate people into districts. We show that unrestrained gerrymandering can severely distort the composition of a legislature, potentially leading half the population to lose all representation of their views. This means that, under majority rule in the congress, gerrymandering enables politicians to enact any legislation of their choice as long as it falls within the interquartile range of the political spectrum. Just as worrisome, gerrymandering can rig any legislation to pass instead of the median policy, which would otherwise prevail in a referendum against any other choice.
This paper examines the welfare implications of third-party informational intermediation. A seller sets the price of a product that is sold through an informational intermediary. The intermediary can disclose information about the product to consumers and earns a fixed percentage of sales revenue in each period. The intermediary’s market base grows at a rate that increases with past consumer surplus. We characterize the stationary equilibria and the set of subgame perfect equilibrium payoffs. When market feedback (i.e., the extent to which past consumer surplus affects future market bases) increases, welfare may decrease in the Pareto sense.
This paper examines the welfare effects of informational intermediation. A (short-lived) seller sets the price of a product that is sold through a (long-lived) informational intermediary. The intermediary can disclose information about the product to consumers, earns a fixed percentage of the sales revenue in each period, and has concerns about its prominence—the market size it faces in the future, which in turn is increasing in past consumer surplus. We characterize the Markov perfect equilibria and the set of subgame perfect equilibrium payoffs of this game and show that when the market feedback (i.e., how much past consumer surplus affects future market sizes) increases, welfare may decrease in the Pareto sense.
A data broker sells market segmentations created by consumer data to a producer with private production cost who sells a product to a unit mass of consumers with heterogeneous values. In this setting, I completely characterize the revenue-maximizing mechanisms for the data broker. In particular, every optimal mechanism induces quasi-perfect price discrimination. That is, the data broker sells the producer a market segmentation described by a cost-dependent cutoff, such that all the consumers with values above the cutoff end up buying and paying their values while the rest of consumers do not buy. The characterization of optimal mechanisms leads to additional economically relevant implications. I show that the induced market outcomes remain unchanged even if the data broker becomes more active in the product market by gaining the ability to contract on prices; or by becoming an exclusive retailer, who purchases both the product and the exclusive right to sell the product from the producer, and then sells to the consumers directly. Moreover, vertical integration between the data broker and the producer increases total surplus while leaving the consumer surplus unchanged, since consumer surplus is zero under any optimal mechanism for the data broker.