Modeling Complex Network Patterns in International Trade

When studying the formation of trade between two countries, traditional modeling has described it as being primarily dependent on individual and bilateral characteristics of the two trading partners. It is likely, however, that trade is dependent not only on the two countries involved but on the patterns by which all countries trade. Standard efforts to control for these complex network dependencies such as the inclusion of multilateral resistance terms in gravity models provide only a blunt reflection of these dependencies and overlook many of their details. This paper describes the explicit incorporation of complex network patterns in trade models. Two types of models are considered: gravity models that incorporate network covariates and exponential random graph models (ERGMs) that analyze trade from a network perspective. Estimates of both models provide evidence that network dependencies are influential in international trade. Comparisons of both models indicate that each approach outperforms the other at capturing and replicating certain types of network patterns. These results indicate that complex network patterns are an important determinant of trade, that gravity models can capture much of this dependency, and that other network models such as ERGMs can be valuable tools for capturing some types of network dependencies