  Suppose agents can exert costly effort that creates nonrival, heterogeneous
benefits for each other. At each possible outcome, a weighted, directed network
describing marginal externalities is defined. We show that Pareto efficient
outcomes are those at which the largest eigenvalue of the network is 1. An
important set of efficient solutions, Lindahl outcomes, are characterized by
contributions being proportional to agents' eigenvector centralities in the
network. The outcomes we focus on are motivated by negotiations. We apply the
results to identify who is essential for Pareto improvements, how to
efficiently subdivide negotiations, and whom to optimally add to a team.
