Modelling Trade Growth for Long-Run Economic Prospects: Improving Trade to Income Elasticity Calibration in Baselines

As a measure of global economic performance, the world trade to income elasticity (a ratio of trade growth to GDP growth) has been estimated to be 1.5 for merchandise trade from 1950 through 2017. Following the recession, this elasticity fell to 1.1 for 2011-2013 as global trade growth stalled, illustrating its importance in reflecting global conditions. In ex-ante research on long-run economic prospects, the projected trade to income elasticity serves as an important indicator for future anticipated global prosperity; however, even in the long-run, model mechanisms deliver an elasticity below 1, much lower than expected. In this paper, we provide a new approach to calibrating the trade to income elasticity to a ratio above 1, as implemented in a new version of the MAGNET (Modular Applied GeNeral Equilibrium Tool) model. As standard in the literature, we take as exogenous GDP growth projections; thus, in our approach we focus on trade growth calibration. Specifically, we allow the model to directly adjust trade flows across sectors, in contrast to the sector-specific targeting for transportation and oil in the literature. Further, while the current state-of the-art calibration methods target the Armington equation, we implement a cost-neutral preference shift, which greatly improves long-run production pathways in the calibrated baseline. Finally, we consider growth in both merchandise trade as well as trade in services, the latter being especially important to capture in long-run ex-ante studies where we anticipate services to play an increasingly important role in the global economy as cross-border digital services become pervasive.