We analyze delinquent networks of adolescents in the United States. We develop a dynamic network formation model showing who the key player is, i.e. the criminal who once removed generates the highest possible reduction in aggregate crime level. We then structurally estimate our model using data...

We study the impact of research collaborations in coauthorship networks on total research output. Through the links in the collaboration network researchers create spillovers not only to their direct coauthors but also to researchers indirectly linked to them. We characterize the interior...

In this paper we introduce a stochastic network formation model where agents choose both actions and links. Neighbors in the network benefit from each other's action levels through local complementarities and there exists a global interaction effect reflecting a strategic substitutability in...

We study the impact of research collaborations in coauthorship networks on research output and how optimal funding can maximize it. Through the links in the collaboration network, researchers create spillovers not only to their direct coauthors but also to researchers indirectly linked to them....

We study the impact of research collaborations in coauthorship networks on research output and how optimal funding can maximize it. Through the links in the collaboration network, researchers create spillovers not only to their direct coauthors but also to researchers indirectly linked to them....

This paper studies the impact of collaboration on research output. First, we build a micro founded model for scientific knowledge production, where collaboration between researchers is represented by a bipartite network. The equilibrium of the game incorporates both the complementarity effect...

We study a structural model of R&D alliance networks in which firms jointly form R&D collaborations to lower their production costs while competing on the product market. We derive the Nash equilibrium of this game, provide a welfare analysis and determine the optimal R&D subsidy program that...

An information matrix of a parametric model being singular at a certain true value of a parameter vector is irregular. The maximum likelihood estimator in the irregular case usually has a rate of convergence slower than the Ín-rate in a regular case. We propose to estimate such models by the...

We model network formation and interactions under a unified framework by considering that individuals anticipate the effect of network structure on the utility of network interactions when choosing links. There are two advantages of this modeling approach: first, we can evaluate whether network...

This paper studies the generalized spatial two stage least squares (GS2SLS) estimation of spatial autoregressive models with autoregressive disturbances when there are endogenous regressors with many valid instruments. Using many instruments may improve the efficiency of estimators...