Research Seminars @ Illinois

Abstract: We incorporate policy competition among governments into a quantitative spatial model. Our new approach quantifies the interdependence of policymaking among a large number of competing jurisdictions, allowing us to fully characterize an endogenous network of potentially millions of bilateral strategic policy linkages. These linkages are summarized by the "policy impact" of each jurisdiction---the extent to which a jurisdiction changing its policy affects policy choices of others. Policy impact is heterogeneous across jurisdictions and the primary driver of the welfare effects of policy competition. We apply our model to a network of 3,109 U.S. counties competing in local sales taxes and evaluate several centralized interventions aimed at limiting tax competition. We find that (1) tax competition is harmful: federal interventions increase welfare, albeit heterogeneously across places; (2) ignoring endogenous policies from a quantitative spatial model underestimates welfare effects by up to 33%. To explore the underlying mechanisms, we rank counties by the magnitude of their policy impact. We show that interventions targeting high-policy impact jurisdictions raise welfare by six times more than targeting low-tax jurisdictions, the standard focus of minimum tax policies. Although policy impact is endogenous, we document that jurisdiction size acts as a strong proxy. Beyond taxation, our framework for endogenizing policy and analyzing its implications extends to tariffs and trade wars, environmental policy competition, regulatory policies, and spending competition.

Policy Competition in a Spatial Economy is the joint work of David Agrawal, Tidiane Ly and Raphael Parchet.