Are speculators driving up oil prices? Should we raise energy prices to slow global warming? The present study takes a small number of such questions and compares the views of economic experts with those of the public. This comparison uses a panel of 2000+ respondents from YouGov with the views of the panel of experts from the IGM at the Chicago Booth School. We found that most of the US population is at best modestly informed about major economic questions and policies. The low level of knowledge is generally associated with the intrusion of ideological, political, and religious views that challenge or deny the current economic consensus. The intruding factors are highly heterogeneous and are much more diverse than the narrowness of public political discourse would suggest. Many of these findings have been established for scientific subjects, but they appear to be equally important for economic views.
We analyze digital markets where a monopolist platform uses data to match multiproduct sellers with heterogeneous consumers who can purchase both on and o§ the platform. The platform sells targeted ads to sellers that recommend their products to consumers and reveals information to consumers about their values. The revenueoptimal mechanism is a managed advertising campaign that matches products and preferences e¢ ciently. In equilibrium, sellers o§er higher qualities at lower unit prices on than o§ the platform. Privacy-respecting data-governance rules such as organic search results or federated learning can lead to welfare gains for consumers.
We develop an auction model for digital advertising. A monopoly platform has access to data on the value of the match between advertisers and consumers. The platform support bidding with additional information and increase the feasible surplus for on-platform matches. Advertisers jointly determine their pricing strategy both on and off the platform, as well as their bidding for digital advertising on the platform.
We compare a data-augmented second-price auction and a managed campaign mechanism. In the data-augmented auction, the bids by the advertisers are informed by the data of the platform regarding the value of the match. This results in a socially efficient allocation on the platform, but the advertisers increase their product prices off the platform to be more competitive on the platform. In consequence, the allocation off the platform is inefficient due to excessively high product prices.
The managed campaign mechanism allows advertisers to submit budgets that are then transformed into matches and prices through an autobidding algorithm. Compared to the data-augmented second-price auction, the optimal managed campaign mechanism increases the revenue of the digital platform. The product prices off the platform increase and the consumer surplus decreases.
We introduce a model of dynamic pricing in perishable goods markets with competition and provide conditions for equilibrium uniqueness. Pricing dynamics are rich because both own and competitor scarcity affect future profits. We identify new competitive forces that can lead to misallocation due to selling units too quickly: the Bertrand scarcity trap. We empirically estimate our model using daily prices and bookings for competing U.S. airlines. We compare competitive equilibrium outcomes to those where firms use pricing heuristics based on observed internal pricing rules at a large airline. We find that pricing heuristics increase revenues (4-5%) and consumer surplus (3%).
Purely affective interaction allows the welfare of an individual to depend on her own actions and on the profile of welfare levels of others. Under an assumption on the structure of mutual affection that we interpret as “non-explosive mutual affection,” we show that equilibria of simultaneous-move affective interaction are Pareto optimal independently of whether or not an induced standard game exists. Moreover, if purely affective interaction induces a standard game, then an equilibrium profile of actions is a Nash equilibrium of the game, and this Nash equilibrium and Pareto optimal profile of strategies is locally dominant.
We propose a demand estimation method that allows for a large number of zero sale observations, rich unobserved heterogeneity, and endogenous prices. We do so by modeling small market sizes through Poisson arrivals. Each of these arriving consumers solves a standard discrete choice problem. We present a Bayesian IV estimation approach that addresses sampling error in product shares and scales well to rich data environments. The data requirements are traditional market-level data as well as a measure of market sizes or consumer arrivals. After presenting simulation studies, we demonstrate the method in an empirical application of air travel demand.
We offer an approach to cooperation in repeated games of private monitoring in which players construct models of their opponents' behavior by observing the frequencies of play in a record of past plays of the game in which actions but not signals are recorded. Players construct models of their opponent's behavior by grouping the histories in the record into a relatively small number of analogy classes for which they estimate probabilities of cooperation. The incomplete record and the limited number of analogy classes lead to misspecified models that provide the incentives to cooperate. We provide conditions for the existence of equilibria supporting cooperation and equilibria supporting high payoffs for some nontrivial analogy partitions.
We study the intergenerational effect of education policy on crime. We use Swedish administrative data that links outcomes across generations with crime records and we show that the comprehensive school reform, gradually implemented between 1949 and 1962, reduced conviction rates both for the generation directly affected by the reform and for their sons. The reduction in conviction rates occurred across many types of crime. Key mediators for this reduction in the child generation are an increase in education and a decline in crime amongst their fathers.
The propensity of consumers to talk after a good versus bad experience with a product can differ based on information available from other marketing channels, for example the brand image or advertising. This can result in selection of positive/negative word-of-mouth for reasons outside of product quality. We develop a unifying framework of WOM, brand image, product advertising, and pricing with a focus on the instrumentality motive of word-of-mouth: early adopters talk to inform new buyers’ purchasing decisions. The different marketing channels shape the information sharing behavior of the early adopter as well as the target consumer’s purchase decision. We show that if the brand image is strong, then in equilibrium only negative WOM can arise. In contrast, with a weak brand image, positive WOM must occur. We also show that holding product quality fixed, a positive advertising signal realization leads to a more positive WOM selection. The model can be applied to both one-one informal WOM as well as online reviews. The assumptions and main predictions of our model are consistent with those that we identified from a primary survey and observational Yelp data.