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 gains from trade liberalization in models with monopolistic competition, firm-level heterogeneity, and variable markups. For a large class of demand functions used in the international macro and trade literature, we derive a parsimonious generalization of the welfare formula in Arkolakis et al. (2012). We then use both estimates from micro-level trade data and evidence regarding firm-level pass through to quantify the implications of this new formula.Within the class of models that we consider, our main finding is that gains from trade liberalization predicted by models with variable markups are equal to, at best, and slightly lower than, at worst, those predicted by models with constant markups. In this sense, pro-competitive effects of trade are elusive.