A rising tide lifts all boats: can InsurTech drive the development of agricultural insurance?—Evidence from the income threshold effect of farmers

With the widespread application of technologies such as artificial intelligence (AI), big data, cloud computing, and the Internet of Things (IoT) in the insurance sector, InsurTech is regarded as a potential solution to address the challenges of underwriting, pricing, and claims processing in agricultural insurance. This paper explores the role of InsurTech in the development of agricultural insurance through the lenses of information asymmetry, technological diffusion, and transaction costs. By integrating theoretical frameworks such as the Bayesian Signal Extraction Model, insurance pricing models, and demand functions, the paper proposes the mechanisms through which InsurTech influences agricultural insurance development and formulates testable hypotheses. Utilizing provincial-level panel data from 31 provinces in China from 2011 to 2023, a two-way fixed effects model is employed to identify the impact of InsurTech on agricultural insurance development. Robustness and endogeneity tests are conducted, including alternative dependent variables, instrumental variable methods, exclusion of pandemic period samples, and propensity score matching (PSM). Furthermore, regional heterogeneity is analyzed by distinguishing between major and non-major grain-producing areas, and a Hansen threshold model is used to examine the nonlinear effect of farmers' disposable income. The results reveal: (1) InsurTech significantly promotes agricultural insurance development; (2) the promotion effect is more pronounced in non-major grain-producing areas; and (3) farmers' disposable income exhibits a “double threshold” effect—when income exceeds approximately 6,008 RMB and 12,842 RMB, the marginal effect of InsurTech's promotion gradually intensifies. This study provides empirical evidence for enhancing the digital infrastructure of agricultural insurance and the development of regionally differentiated policies.