Targeting network intervention with social norm

Abstract

This paper discusses a network game in a local-average setup, where players' payoffs depend on the social norms they confront. I focus on an optimal targeting intervention problem, where a planner aims to maximize social welfare by altering individual characteristics ex ante. First, I decompose orthogonally the optimal intervention into the eigenspaces of the social welfare matrix. In what follows, I present the limit forms of the optimal intervention as the budget approaches infinity or zero. I then identify the errors arising from approximating the optimal intervention by its various limit forms. Finally, this paper explores the intervention problem under incomplete information, where the planner switches from mean to variance intervention based on the comparison of their unit costs and the aggregate budget size.