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...

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...

We develop a tractable dynamic model of productivity growth and technology spillovers that is consistent with the emergence of real world empirical productivity distributions. Firms can improve productivity by engaging in in-house R\&D, or alternatively, by trying to imitate other firms'...