Estimating Border Effects: The Impact of Spatial Aggregation

Abstract

Trade data are typically reported at the level of regions or countries and are therefore aggregates across space. In this paper, we investigate the sensitivity of standard gravity estimation to spatial aggregation. We build a model in which initially symmetric micro regions are combined to form aggregated macro regions. We then apply the model to the large literature on border effects in domestic and international trade. Our theory shows that larger countries are systematically associated with smaller border effects. The reason is that due to spatial frictions, aggregation across space increases the relative cost of trading within borders. The cost of trading across borders therefore appears relatively smaller. This mechanism leads to border effect heterogeneity and is independent of multilateral resistance effects in general equilibrium. Even if no border frictions exist at the micro level, gravity estimation on aggregate data can still produce large border effects. We test our theory on domestic and international trade flows at the level of U.S. states. Our results confirm the model's predictions, with quantitatively large effects.