We analyze a model of R&D alliance networks where firms are engaged in R&D collaborations that lower their production costs while competing on the product market. We provide a complete characterization of the Nash equilibrium and determine the optimal R&D subsidy program that maximizes total welfare. We then structurally estimate this model using a unique panel of R&D collaborations and annual company reports. We use our estimates to study the impact of targeted versus nondiscriminatory R&D subsidy policies and empirically rank firms according to the welfare-maximizing subsidies they should receive.

We develop a model of market entry under social learning through word of mouth (WOM). The success of an entrant depends on consumer awareness generated via WOM, modeled as a percolation process on a random graph. The likelihood of an entrant gaining significant awareness depends on network structure, characterized by the first three factorial moments of the degree distribution. We identify three pricing equilibria: blockaded, deterred, and accommodated entry. The model demonstrates that increased network density can shift equilibria from blockaded to deterred and eventually to accommodated entry. Numerical simulations suggest that consumer surplus may be nonmonotonic with respect to network density. Additionally, if incumbents can charge personalized prices based on consumers' connectivity, they may optimally set lower prices for highly connected consumers.

We propose a model of intergenerational transmission of education wherein children belong to either highly educated or low-educated families. Children choose the intensity of their social activities, while parents decide how much educational effort to exert. Using Add Health data, we find that, on average, children’s homophily acts as a complement to the educational effort of highly educated parents but as a substitute for the educational effort of low-educated parents. We also find that policies that subsidize kids’ socialization efforts can backfire for low-educated students because they tend to increase their interactions with other low-educated students.

There is substantial empirical evidence showing that peer effects matter in many activities. The workhorse model in empirical work on peer effects is the linear‐in‐means (LIM) model, whereby it is assumed that agents are linearly affected by the mean action of their peers. We develop a new general model of peer effects that relaxes the linear assumption of the best‐reply functions and the mean peer behavior and that encompasses the spillover, conformist model, and LIM model as special cases. Then, using data on adolescent activities in the United States, we structurally estimate this model. We find that for many activities, individuals do not behave according to the LIM model. We run some counterfactual policies and show that imposing the mean action as an individual social norm is misleading and leads to incorrect policy implications.

We examine how social interactions and friendships shape students' political opinions in a natural experiment at Sciences Po, a leading French university specializing in social and political sciences. The quasi-random assignment of students into short-term integration groups before their academic curriculum reduces political opinion gaps and fosters friendship formation. Using same-group membership as an instrumental variable for friendship, we find that friendship reduces opinion differences by 40% of a standard deviation in the opinion gap. Our evidence supports a homophily-enforced mechanism: friendships form among initially politically similar students, leading them to join political associations together, reinforcing their similarity. However, friendship does not significantly influence politically dissimilar pairs. Instead, it reduces opinion divergence without enforcing ideological convergence.