This paper analyzes the formation of networks in which each agent is assumed to possess some information of value to the other agents in the network. Agents derive payoff from having access to the information of others through communication or spillovers via the links between them. Linking...

This paper analyzes the formation of networks in which each agent is assumed to possess some information of value to the other agents in the network. Agents derive payoff from having access to the information of others through communication or spillovers via the links between them. Linking...

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...

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...

In a social network, agents have their own reference group which may influence their behaviour. In turn, the agents' attributes and their behaviour affect the formation and the structure of the social network. This paper surveys the econometric literature on both aspects of social networks, 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...

We develop a dynamic network formation model that can explain the observed nestedness in real-world networks. Links are formed on the basis of agents' centrality and have an exponentially distributed life time. We use stochastic stability to identify the networks to which the network formation...

We develop a dynamic network formation model that can explain the observed nestedness in real-world networks. Links are formed on the basis of agents' centrality and have an exponentially distributed life time. We use stochastic stability to identify the networks to which the network formation...

We develop a dynamic network formation model that can explain the observed nestedness in real-world networks. Links are formed on the basis of agents' centrality and have an exponentially distributed life time. We use stochastic stability to identify the networks to which the network formation...

Counterfactual policy evaluation often requires computation of game-theoretic equilibria. We provide new algorithms for computing pure-strategy Nash equilibria of games on networks with finite action spaces. The algorithms exploit the fact that many agents may be endowed with types such that a...