Examining the role of border protectionism in border inspections: panel structural vector autoregression evidence from FDA import refusals on China's agricultural exports

Purpose: As technical barriers gradually become the important tools of trade protection, it is important to understand whether intensified enforcement of border controls is adopted as a hidden tool of trade protectionism and differs across periods and industries. Design/methodology/approach: This article applies a panel structural vector autoregression (PSVAR) model to investigate the potential role of trade protectionism motives in Food and Drug Administration (FDA) import refusals on China's agricultural exports, utilizing newly constructed monthly data at the industry level. Findings: The results show that import refusal is mainly driven by the inspection history, highlighting the importance of the intrinsic product quality and maintaining an excellent inspection history in border inspection. The novel finding is that US employment contractions would also lead to a small increase in FDA import refusals, especially those taking place within ten months and made without sampling tests. Such an association is driven by industry-specific employment shocks and becomes stronger after the financial crisis. It is also more evident in industries where the US lacks competitiveness against China, being manufactured without mandatory safety regulations, and with negative skewness of employment growth. Originality/value: This research is one of the preliminary attempts to understand whether the de facto border controls are worked as a hidden tool of protectionism to agricultural products, and what the specific trajectory and duration of the impacts at the monthly level. This study provides empirical evidence showing the role of protectionism motives in FDA import refusals and is heterogeneous across industries, which generate new insights and policy implications to predict and cope with additional barriers on agricultural trade.