Impacts of COVID-19 Non-pharmaceutical Interventions on Trade Flows: A Global Panel Vector Autoregression Analysis

Abstract

The COVID-19 outbreak has contributed to a tremendous global decline in international trade flows. The rapid spread of the disease and the control measures implemented by governments to contain the virus have led to serious consequences for the global economy. The pandemic has affected the international movement of people, goods, and services. Currently, the systematic quantitative research investigating the effects of specific non-pharmaceutical intervention policy clusters on country-level international trade flows, remains limited. In this study, the Panel Vector Autoregression (PVAR) method was conducted using country-level panel data collected from various international sources including the United Nations, World Bank, and University of Oxford. The results show that stringent COVID-19 closure, social distancing, and containment measures and health-related measures, had significant negative impacts on trade flows. In contrast, economic support measures showed significant positive effects on trade. In summary, the findings suggest that policymakers should maintain less stringent containment measures related to public closure and movement restrictions and stimulate economic activities through economic support policies in order to minimize losses in trade flows during the pandemic.