Quantifying data manipulation of food inspection agencies: evidence from food safety supervision sampling in China

PurposeFood safety supervision sampling is a critical tool for governments to identify problematic foods and enterprises, yet its problem-identification capability falls short of expectations. In this regard, existing literature has primarily focused on the impact of government behavior in the sampling process, neglecting potential data manipulation by food inspection agencies during the testing phase. This study aims to address this critical gap by identifying and quantifying the manipulation of food inspection agencies.Design/methodology/approachUsing a dataset of 71,898 unqualified samples published by market supervision departments across 30 Chinese provinces from 2018 to 2023, this paper examines the distribution of non-compliant samples near the qualified standard value using exceedance multiples. To quantify the extent of data manipulation, this study employs an exhaustive algorithm to construct counterfactual estimates.FindingsThis paper identifies an abnormal distribution of unqualified samples near standard value, indicating potential data manipulation. Robustness tests further corroborate this inference. Approximately 11.17% of unqualified samples may have been adjusted to qualified status during 2018–2023, with higher manipulation rates in eastern regions than in central and western regions. The manipulation rate of unqualified samples across 25 sample provinces ranges from 8.13% to 16.30%.Originality/valueData manipulation of food inspection agencies is a critical yet underexplored issue in food safety supervision sampling. This study fills this gap and estimates the extent of manipulation in provincial-level food safety sampling in China. Our findings offer novel insights for improving the efficiency of sampling and actionable policy recommendations to strengthen governmental oversight of inspection agencies.