High Trade Costs and Their Consequences: An Estimated Dynamic Model of African Agricultural Storage and Trade

How large are trade costs in the world’s poorest countries and what are their consequences? I explore this question using a new dataset of monthly prices and production of 6 staple grains from 2003 to 2013 in 230 market catchment areas covering all 42 countries of continental subSaharan Africa. Using a new approach to identify cost parameters when trade and storage are unobserved, I estimate and solve a dynamic model including storage in each of the 230 markets, overland trade between them, and trade with the world market through 30 ports. I find median intra-national trade costs over 5 times higher than elsewhere in the world along with significant extra costs for trade across borders and with the world market. I then simulate a counterfactual in which trade costs for staple grains are lowered to match an international benchmark. Lowering trade costs results in a 46% drop in the average food price index, a 42% loss of net agricultural revenues, and a welfare gain equivalent to 2.2% of GDP. I show that 86% of this welfare gain can be achieved by lowering trade costs through ports and along key links representing just 18% of the trade network, supporting a corridor-based approach for infrastructure investment and trade policy. In an extension, I find that the effects of agricultural technology adoption depend crucially on trade costs, with technology adoption increasing farmer incomes only when trade costs are low. Compared to my dynamic monthly model with storage, a static annual model of agricultural trade underestimates trade costs by 23% and welfare effects by 33% by failing to correctly identify when trade occurs.