This paper studies consumers' privacy choices when firms can use their data to make personalized offers. We first introduce a general framework of personalization and privacy choice, and then apply it to personalized recommendations, personalized prices, and personalized product design. We argue that due to firms' reaction in the product market, consumers who share their data often impose a negative externality on other consumers. Due to this privacy-choice externality, too many consumers share their data relative to the consumer optimum; moreover, more competition, or improvements in data security, can lower consumer surplus by encouraging more data sharing.
This paper identifies a set of possible regulations that could be used both to make the search market more competitive and simultaneously ameliorate the harms flowing from Google’s current monopoly position. The purpose of this paper is to identify conceptual problems and solutions based on sound economic principles and to begin a discussion from which robust and specific policy recommendations can be drafted.
We study personalized pricing (or first-degree price discrimination) in a general oligopoly model. In the short-run, when the market structure is fixed, the impact of personalized pricing hinges on the degree of market coverage (i.e., how many consumers buy). If coverage is high (e.g., because the production cost is low, or the number of firms is large), personalized pricing intensifies competition and so harms firms but benefits consumers, whereas the opposite is true if coverage is low. However in the long-run, when the market structure is endogenous, personalized pricing always benefits consumers because it induces the socially optimal level of firm entry. We also study the asymmetric case where some firms can use consumer data to price discriminate while others cannot, and show it can be worse for consumers than when either all or no firms can personalize prices.
We study personalized pricing in a general oligopoly model. When the market structure is fixed, the impact of personalized pricing relative to uniform pricing hinges on the degree of market coverage. If market conditions are such that coverage is high, personalized pricing harms firms and benefits consumers, whereas the opposite is true if coverage is low. However, when the market structure is endogenous, personalized pricing benefits consumers because it induces socially optimal firm entry. Finally, when only some firms have data to personalize prices, consumers can be worse off compared to when either all or no firms personalize prices.
This paper studies competition between firms when consumers observe a private signal of their preferences over products. Within the class of signal structures that induce pure-strategy pricing equilibria, we derive signal structures that are optimal for firms and those that are optimal for consumers. The firm-optimal policy amplifies underlying product differentiation, thereby relaxing competition, while ensuring consumers purchase their preferred product, thereby maximizing total welfare. The consumer-optimal policy dampens differentiation, which intensifies competition, but induces some consumers to buy their less preferred product. Our analysis sheds light on the limits to competition when the information possessed by consumers can be designed flexibly.
This paper identifies a set of possible regulations that could be used both to make the search market more competitive and simultaneously ameliorate the harms flowing from Google’s current monopoly position. The purpose of this paper is to identify conceptual problems and solutions based on sound economic principles and to begin a discussion from which robust and specific policy recommendations can be drafted.
This paper proposes a framework for studying competitive mixed bundling with an arbitrary number of firms. We examine both a firm’s incentive to introduce mixed bundling and equilibrium tariffs when all firms adopt the mixed-bundling strategy. In the duopoly case, relative to separate sales, mixed bundling has ambiguous impacts on prices, profit and consumer surplus; with many firms, however, mixed bundling typically lowers all prices, harms firms and benefits consumers.
This paper studies competition between firms when consumers observe a private signal of their preferences over products. Within the class of signal structures which induce pure-strategy pricing equilibria, we derive signal structures which are optimal for firms and those which are optimal for consumers. The firm-optimal policy amplifies underlying product differentiation, thereby relaxing competition, while ensuring consumers purchase their preferred product, thereby maximizing total welfare. The consumer-optimal policy dampens differentiation, which intensifies competition, but induces some consumers to buy their less-preferred product. Our analysis sheds light on the limits to competition when the information possessed by consumers can be designed flexibly.
We propose a model of how multiple societies respond to a common crisis. A government faces a “damned-either-way” policy-making dilemma: aggressive intervention contains the crisis, but the resulting good outcome makes people skeptical of the costly response; light intervention worsens the crisis and causes the government to be faulted for not doing enough. This dilemma can be mitigated for the society that encounters the crisis first if another society faces the same crisis afterward. Our model predicts that the later society does not necessarily perform better despite having more information, while the earlier society might benefit from a dynamic counterfactual effect.
We propose a model of how multiple societies respond to a common crisis. A government faces a "damned-either-way" policymaking dilemma: aggressive intervention contains the crisis, but the resulting good outcome makes people skeptical about the costly response; light intervention worsens the crisis and causes the government to be faulted for not doing enough. When multiple societies encounter the crisis sequentially, due to this policymaking dilemma, late societies may underperform despite having more information, while early societies can benefit from a dynamic counterfactual effect.
Open banking facilitates data sharing consented by customers who generate the data, with a regulatory goal of promoting competition between traditional banks and challenger fintech entrants. We study lending market competition when sharing banks’ customer data enables better borrower screening or targeting by fintech lenders. Open banking could make the entire financial industry better off yet leave all borrowers worse off, even if borrowers could choose whether to share their data. We highlight the importance of equilibrium credit quality inference from borrowers’ endogenous sign-up decisions. When data sharing triggers privacy concerns by facilitating exploitative targeted loans, the equilibrium sign-up population can grow with the degree of privacy concerns.