We study the efficiency of decentralized team formation inside research organizations through the lens of a one-sided matching model with non-cooperative after-match information production. In our model, inefficient sorting arises from two sources. First, moral hazard within teams may cause workers to join less productive teams in which they exert relatively less effort. Second, even if productive teams form, such teams may reduce average productivity across all teams. We identify management interventions that restore efficiency.
I study how a monopolist data broker (seller), who wants to maximize profits, should present and sell consumer data to a firm (buyer). The buyer has an interest in forecasting a particular consumer characteristic, but the seller is uncertain about which characteristic the buyer wants to forecast and how much the buyer values information. I assume that the joint distribution of both the unknown characteristics and the data is elliptical. This information environment reduces to a multidimensional, multi-product mechanism design problem in which the buyer’s payoffs are nonlinear. Hence, I cannot use the common differential approach to solve for the optimal mechanism. I obtain two main results. First, I show that the seller should optimally offer statistics that are linear combinations of the data and independent noise. Second, by using a direct approach, I show that in the optimal mechanism the seller might want to offer a continuum of different statistics, and these statistics, without containing independent noise, are less correlated than they would be if the seller could perfectly price discriminate. Thus this distortion affects the mimicking type more than the mimicked type.
I study endogenous network formation in an environment in which individuals want to forecast a stochastic state and it is costly for them to communicate with others to exchange some exogenously observed information. Due to the existence of information complementarities, individuals’ preferences for networks in which they have multiple neighbors cannot be characterized by a linear ranking of the pairwise correlations between their signals. Instead, these complementarities generate a counterintuitive result: for a fixed number of individuals, information structures exist in which all signals are conditionally positively correlated, and these are preferred to a structure in which all signals are conditionally independent. Therefore, it may be that the only strongly stable network consists of two cliques with signals that are highly positively correlated within each clique that generate different beliefs across cliques, even when there are opportunities to exchange information with individuals sharing less correlated signals. Thus, this model exemplifies how homophily and belief polarization can coexist in a rational environment.