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)

We develop a model with many advertisers (products) and many advertising markets (media). Each advertiser sells to a di¤erent segment of consumers, and each medium is targeting a di¤erent 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 consumerproduct matches, and hence in the social value of advertising. Yet, targeting also increases the concentration of …rms advertising in each market. Surprisingly, we then …nd that the equilibrium price of advertisements is …rst increasing, then decreasing in the targeting capacity.We trace out the implications of targeting for competing media. We distinguish o-ine and online media by their targeting ability: low versus high. As consumers' relative exposure to online media increases, the revenues of o-ine media decrease, even though the price of advertising might increase.

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 o¤ers 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.Keywords: information design, price of information, statistical experiments, mechanism design, price discrimination, hypothesis testing.JEL Codes: D42, D82, D83.We thank the co-editor, Je¤ Ely, and three anonymous referees for their productive suggestions. We are grateful for conversations with Ben Brooks,

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partially supports the AAMC Faculty Roster under contract HHSN263200900009C. All errors are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.