Policy Innovation in Local Jurisdictions: Testing the Neighborhood Influence Against the Free-Riding Hypothesis

Before making difficult decisions, individuals tend to collect information on decision makers in reference groups. With respect to policy innovations in a decentralized public sector, this may give rise to positive neighborhood influence on adoption decisions. On the other hand, due to learning externalities, an incentive exists to free-ride on policy experiments of others. In this paper, U.S. data on school district policies are used to show that with respect to policy experiments, decision makers indeed are heavily affected by decision makers in reference groups. The results suggest that if a given district's neighbors' expected benefits from adopting a new policy increase, this substantially increases the original district's probability of adoption. The paper thus rejects the free-riding hypothesis and supports the view that in federal systems the diffusion of policy innovations is stimulated by horizontal interactions between jurisdictions.