What do recent advances in economic geography teach us about the spatial distribution of economic activity? We show that the equilibrium distribution of economic activity can be determined simply by the intersection of labor supply and demand curves. We discuss how to estimate these curves and highlight the importance of global geography—the connections between locations through the trading network—in determining how various policy relevant changes to geography shape the spatial economy.
Each year in the US, hundreds of billions of dollars are spent on transportation infrastructure and billions of hours are lost in traffic. We develop a quantitative general equilibrium spatial framework featuring endogenous transportation costs and traffic congestion and apply it to evaluate the welfare impact of transportation infrastructure improvements. Our approach yields analytical expressions for transportation costs between any two locations, the traffic along each link of the transportation network, and the equilibrium distribution of economic activity across the economy, each as a function of the underlying quality of infrastructure and the strength of traffic congestion. We characterize the properties of such an equilibrium and show how the framework can be combined with traffic data to evaluate the impact of improving any segment of the infrastructure network. Applying our framework to both the US highway network and the Seattle road network, we find highly variable returns to investment across different links in the respective transportation networks, highlighting the importance of well-targeted infrastructure investment.
We study the theoretical properties and counterfactual predictions of a large class of general equilibrium trade and economic geography models. By combining aggregate factor supply and demand functions with market-clearing conditions, we prove that existence, uniqueness, and—given observed trade flows—the counterfactual predictions of any model within this class depend only on the demand and supply elasticities (“gravity constants”). Using a new “model-implied” instrumental variables approach, we estimate these gravity constants and use these estimates to compute the impact of a trade war between the United States and China.