Trade with Correlation

The paper develops a trade model in which productivity—the result of a country’s ability to adopt global technologies—presents an arbitrary pattern of spatial correlation. The model generates the full class of import demand systems consistent with Ricardian theory, and, hence, captures its full macroeconomic implications. In particular, the framework formalizes Ricardo’s insight—absent from the canonical Ricardian model—that countries gain more from trade partners with relatively dissimilar technology. Incorporating this insight into the calculations of macro counterfactuals entails a simple correction to self-trade shares. The framework enables general aggregation results which tie micro optimization to macro demand systems and guide counterfactual analysis based on micro estimates. The quantitative application to a multi-sector trade model suggests that countries specialized in low correlation sectors have 40 percent higher gains from trade relative to countries specialized in high correlation sectors. After accounting for correlation, the model predicts that lower trade costs for imports from China, rather than Canada, have the largest impact on real wages in the United States.