We study a sequential-learning model featuring a network of naive agents with Gaussian information structures. Agents apply a heuristic rule to aggregate predecessors' actions. They weigh these actions according the strengths of their social connections to different predecessors. We show this...

We address the problem of a planner looking for the efficient network when agents play a network game with local complementarities and links are costly. We show that for general network cost functions, efficient networks belong to the class of Nested-Split Graphs. Next, we refine our results and...

This paper develops a simple model in which a social hierarchy emerges endogenously when agents form a network for complementary interaction (``activity''). Specifically, we assume that agents are ex ante identical and their best response activity, as well as their value function, increases...

A key obstacle to coordination and cooperation in many networked environments is that behavior in each bilateral relationship is not observable to individuals outside that relationship: that is, information is local. This paper investigates when players can use communication to replicate any...

I develop a model of collaboration between tournament participants in which agents collaborate in pairs, and an endogenous structure of collaboration is represented by a weighted network. The agents are forward-looking and capable of coordination; they value collaboration with others and higher...