Collaboration in Bipartite Networks

This paper proposes a general framework for studying the impact of collaboration on team production. We build a micro-founded model for team production, where collaboration between agents is represented by a bipartite network. The Nash equilibrium of the game incorporates both the complementarity effect between collaborating agents and the substitutability effect between concurrent projects of the same agent. We propose a Bayesian DMH procedure to estimate the structural parameters and illustrate the empirical and policy relevance of the model by analyzing the collaboration network of inventors in the semiconductor and pharmaceutical industries.