Food Safety Regulatory Enforcement in China: A Data-Driven Approach

Abstract

Government regulations have a substantial impact on food safety, both within China and elsewhere in the world. But regulatory research is hampered by a lack of systematic data. Much of the extant regulatory research is based on interpretations of government policy and regulatory announcements. At best, qualitative analysis indicates policy and regulatory intent, not enforcement, and it lacks precision and specificity. Using natural language processing (NLP), this study creates quantitative indicators of food regulatory enforcement by the Chinese government based on the conversion of 28,000 free-form criminal-court case texts. We focus on two main Chinese regulatory agencies, the China Food and Drug Administration (CFDA) and the Ministry of Agriculture (MOA). Our quantitative analysis reveals substantial differences in the regulatory functions of these two agencies. The CFDA has been far more proactive than the MOA in uncovering food-safety problems — a function we call a “lead function” — whereas the MOA has been mainly involved in providing evidence and data — a function we call a “supporting function.” To our knowledge, this article is the first to quantitatively map the Chinese government’s regulatory functions in the food industry at such a granular level. The policy implications of our findings are drawn from two contextual factors. First, a large number of China’s food-safety problems occur in the upstream sector — the sector over which the MOA exercises regulatory authority. Second, the Chinese government’s regulatory regime has mainly focused on the CFDA rather than the MOA. These findings suggest a pressing need for the MOA to undertake more lead functions.