Effects of COVID-19 on Trade Flows in the Presence of Ethnic Dissimilarity

Abstract This paper explores the impacts of COVID-19 on the bilateral trade flows in the presence of ethnic distances. I use the distance-adjusted ethno linguistic fractionalization index (DELF) to measure ethnic proximity and the monthly trade data developed by the International Monetary Fund (IMF). I find that within a country pair with larger ethnic distances, an increase in COVID-19 cases in the exporter negatively affects export volume significantly. Considering other things remain the same, I find that a ten percent increase in COVID-19 cases in the exporting country is linked to a 0.0376 percent greater decline in export volume when the ethnic composites of the two countries are completely heterogeneous than when they are entirely homogeneous. If so, governments should consider strategies to promote trade, lower transaction costs, and trade barriers between nations with greater ethnic differences. Failure to fully realize recovery potential will probably result in an inefficient recovery process and an unequal distribution of resources. The result provides insight into the post-pandemic period for policy making. It is reasonable to predict that a larger ethnic distance within a country pair will also impact trade volume in the recovery period if it is causing a more significant decline in trade in response to COVID-19 cases in the exporter.