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

The focus of this paper is the endogenous formation of peer groups. We study a model in which agents choose their peers prior to making decisions on multiple issues. Agents differ in how much they value the decision outcomes on one issue relative to another. While each individual can collect...

We analyze the link between entry and R&D spending distribution. We consider a monopolistic competitive market with free entry in which firms can invest in cost-cutting R&D by paying a fixed cost first. For an intermediate level of fixed cost, there is a unique equilibrium in which the market...

This paper uses a new data set on child-adoption matching to estimate the preferences of potential adoptive parents over U.S.-born and unborn children relinquished for adoption. We identify significant preferences favoring girls and unborn children close to birth, and against African-American...

I analyze the R&D investment of firms that decide between outsourcing and in-house production when information leakage is present (contractors learn clients' technology and can diffuse it to competitors)in a general equilibrium model. Information leakage tends to concentrate the outsourcing...

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...