Suchergebnisse

An organization must select among competing projects that differ in their payoff consequences for its members. Each agent chooses a project and exerts effort affecting its completion time. When one or more projects are complete, the agents select which one to adopt. The selection rule for multiple projects that maximizes ex post welfare leads to inefficiently high polarization; rules that favor later proposals improve upon ex post optimal selections. The optimal degree of favoritism increases in the cost of effort and discount rate. This trade-off informs the design of process rules in standard-setting organizations and helps explain their performance. (JEL C78, D23, D71, D72, D83, L15)

We develop a model with many advertisers (products) and many advertising markets (media). Each advertiser sells to a different segment of consumers, and each medium is targeting a different audience. We characterize the competitive equilibrium in the advertising markets and evaluate the implications of targeting. An increase in targeting leads to an increase in the total number of consumer‐product matches, and hence in the social value of advertising. Yet, targeting also increases the concentration of firms advertising in each market. Surprisingly, we then find that the equilibrium price of advertisements is first increasing, then decreasing, in the targeting capacity. We trace out the implications of targeting for competing media. We distinguish offline and online media by their targeting ability: low versus high. As consumers' relative exposure to online media increases, the revenues of offline media decrease, even though the price of advertising might increase.

This paper examines moral hazard in teams over time. Agents are collectively engaged in a project whose duration and outcome are uncertain, and their individual efforts are unobserved. Free-riding leads not only to a reduction in effort, but also to procrastination. Collaboration among agents dwindles over time, but does not cease as long as the project has not succeeded. In addition, the delay until the project succeeds, if it ever does, increases with the number of agents. We show why deadlines, but not necessarily better monitoring, help to mitigate moral hazard. (JEL D81, D82, D83)

The goal of this paper is twofold: First, to develop an estimable model of legislative politics in the US Congress, second, to provide a greater understanding of the objectives behind the New Deal. In the theoretical model, the distribution of federal funds across regions of the country is the outcome of bargaining game in which the President acts as the agenda-setter and Congress bargains over the final shape of the spending bill. For any given preferences (of the President) and distribution of seats in Congress, the model delivers a unique predicted allocation. Combined with data on New Deal programs, this is used to estimate the objectives of the Roosevelt administration. The results indicate that economic concerns for relief and recovery, though not necessarily for fundamental reform and development, largely drove New Deal spending. Political concerns also mattered, but more on the margin.

AbstractA data intermediary acquires signals from individual consumers regarding their preferences. The intermediary resells the information in a product market wherein firms and consumers tailor their choices to the demand data. The social dimension of the individual data—whereby a consumer's data are predictive of others' behavior—generates a data externality that can reduce the intermediary's cost of acquiring the information. The intermediary optimally preserves the privacy of consumers' identities if and only if doing so increases social surplus. This policy enables the intermediary to capture the total value of the information as the number of consumers becomes large.

A data buyer faces a decision problem under uncertainty. He can augment his initial private information with supplemental data from a data seller. His willingness to pay for supplemental data is determined by the quality of his initial private information. The data seller optimally offers a menu of statistical experiments. We establish the properties that any revenue-maximizing menu of experiments must satisfy. Every experiment is a non-dispersed stochastic matrix, and every menu contains a fully informative experiment. In the cases of binary states and actions, or binary types, we provide an explicit construction of the optimal menu of experiments. (JEL D42, D81, D82, D83)