Targeting in Adaptive Networks

This paper studies optimal targeting policies, which consist of eliminating (preserving) a set of agents in a network and aim to minimize (maximize) aggregate effort levels. Unlike the existing literature, we allow the equilibrium network to adapt after a network intervention. We introduce a novel and tractable adjustment process. If global strategic substitution effects are sufficiently small, optimal targeting is characterized by a simple rule: eliminate a set of agents with the highest degree. However, if global strategic substitution effects are large, it may be optimal to target the least central agent or eliminate fewer agents than possible.