Trade with Correlation
Nelson Lind and
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Nelson Lind: Emory University
Natalia Ramondo: UCSD
No 627, 2018 Meeting Papers from Society for Economic Dynamics
We develop 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, our 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. We also present aggregation results that tie micro-optimization to macro demand systems and guide counterfactual analysis based on micro estimates. Our quantitative application using 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.
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