The effects of agglomeration on tax competition: evidence from a two-regime spatial panel model on French data

This article studies how agglomeration economies affect tax competition between local jurisdictions. We develop a theoretical model with two main testable predictions: in a setting where agglomeration forces lessen the responsiveness of capital to tax, high-regime agglomeration jurisdictions should adopt a rent-taxing behavior, and they should react less to their neighbors’ tax policies. The panel dataset spans the period from 1995 to 2007 and focuses on the local business taxes set at the French mid-subnational jurisdiction level of départements. First, instrumental variables estimates indicate that attractive jurisdictions capture a significant part of firms’ agglomeration rent by levying higher tax rates. An increase by 1% of the localization economies indicator (a specialization index) leads to increasing the business tax rate by 0.43%. Second, local tax setting behaviors are characterized by a mimetic behavior, with best response functions that slope upwards. We propose a two-agglomeration-regime spatial lag model to estimate through ML the relationship between tax competition and attractiveness. Our main result shows that both are linked and tax mimicry is less pronounced if a jurisdiction is agglomerated. Specifically, in response to a decrease in the tax rate of neighboring local governments by 1%, local governments with strong agglomeration economies reduce their tax rate by 0.4% against 0.6% for local government characterized by a low-agglomeration regime. We show that the classical one-size-fits-all-case of a single regime of agglomeration suffers from a 40% downward bias for low-agglomeration jurisdictions. We draw the link to policy praxis by discussing the optimal design of equalization schemes.     

A model of the U.S. food system: What are the determinants of the state vulnerabilities to production shocks and supply chain disruptions?

We adapt a Ricardian general equilibrium model to the setting of U.S. domestic agri-food trade to assess states’ vulnerability to adverse production shocks and supply chain disruptions. To this end, we analyze how domestic crop supply chains depend on fundamental state-level comparative advantages—which reflect underlying differences in states’ cost-adjusted productivity levels—and thereby illustrate the capacity of states to adapt to and mitigate the impacts of such disruptions to the U.S. agricultural sector. Based on the theoretical framework and our estimates of the model's structural parameters obtained using data on U.S. production, consumption, and domestic trade in crops, we undertake simulations to characterize the welfare implications of counterfactual scenarios depicting disruptions to (1) states’ agricultural productive capacity, and (2) interstate supply linkages. Our results emphasize that the distributional impacts of domestic supply chain disruptions hinge on individual states’ agricultural productive capacities, and that the ability of states to mitigate the impacts of adverse production shocks through trade relies on the degree to which states are able to substitute local production shortfalls by sourcing crops from other states.