Modelling global trade flows: results from a GVAR model

This paper uses a Global Vector Auto-Regression (GVAR) model featuring 21 emerging market and advanced economies to investigate the factors behind the dynamics of global trade flows, with a particular view on the issue of global trade imbalances and on the conditions of their unwinding. The GVAR approach enables us to make two key contributions: first, to model international linkages among a large number of countries, which is a key asset given the diversity of countries and regions involved in global imbalances, and second, to model exports and imports jointly. The latter proves to be very important due to the internationalization of production chains. The model can be used to gauge the effect on trade flows of various scenarios, such as an output shock in the United States, a shock to the US real effective exchange rate and shocks to foreign (e.g., German and Chinese) variables. Results indicate that changes in domestic and foreign demand have a much stronger effect on trade flows than changes in relative trade prices. In addition, we show how the model can be used to monitor trade developments, with an application to the Great Trade Collapse.