The focus of this paper is the endogenous formation of peer groups. In our model, agents choose peers before making contributions to public projects, and they differ in how much they value one project relative to another. Thus, the groups preference composition affects the type of contributions...

We examine how the structure of terror networks varies with legal limits on interrogation and the ability of authorities to extract information from detainees. We assume that terrorist networks are designed to respond optimally to a trade-off caused by information exchange: Diffusing information...

In criminal organizations, diffusing information widely throughout the organization might lead to greater internal efficiency (in particular, since these organizations are self-sustaining, through facilitating cooperation). However, this may come at a cost of leaving the organization more...

We study the effects of network externalities on a unique matching protocol for faculty in a large U.S. professional school to offices in a new building. We collected institutional, web, and survey data on faculty's attributes and choices. We first identify the different layers of the social...

In this paper we study the incentives of firms to promote innovation. We analyze a situation in which an employee in a firm is inspired with a new idea for a product. In a framework in which Intellectual Property Rights on ideas are imperfect, we analyze the employee's decision of whether to...

This paper uses a new data set on domestic child adoption to document the preferences of potential adoptive parents over born and unborn babies relinquished for adoption by their birth mothers. We show that adoptive parents exhibit significant biases in favor of girls and against...

This paper uses a new data set on domestic child adoption to document the preferences of potential adoptive parents over born and unborn babies relinquished for adoption by their birth mothers. We show that adoptive parents exhibit significant biases in favor of girls and against...