The implementation of the agricultural insurance policy and advancement of agricultural technology has great significance for the development of the agricultural economy of China, and it is an important source of national stability and modernization and development of the agriculture sector. Agricultural insurance policy uses the expansion of agricultural technology progress in the process of evaluation, investigation and claims settlement, and so on. Agricultural technology progress is effective in the reduction of some agricultural risks, it also affects farmers’ agricultural insurance behaviors, and optimizes the operating environment of agricultural insurance. The objective of this research is to explore the relationship between agricultural technology progress, agricultural insurance and farmers’ income. It also explains the mutual/cooperative relationship between agricultural technology progress and agricultural insurance. It provides the theoretical basis and data support to verify the promotion effect of agricultural insurance and agricultural technology progress on farmers’ income. This gives the improvement path for alleviating the spatial imbalance of China’s agricultural development. Keeping in view the aforementioned background and this research explores the effects of agricultural technological progress and agricultural insurance on the farmers’ income level. The panel data used for this research were from 2004 to 2019 and were grouped into two parts: high-density agricultural insurance areas and low-density agricultural insurance areas. The relationship between agricultural technology progress, agricultural insurance and farmers’ income was estimated using the Panel Vector Autoregressive (PVAR) model. The results revealed that: (i) both agricultural technology progress and agricultural insurance have a positive effect on the farmers’ income level, but this effect varies across regions; (ii) impact of the agricultural insurance on farmers’ income is greater than the impact of agricultural technology progress on farmers’ income; and (iii) the role of agricultural insurance in promoting agricultural technology progress exists only in areas with high-density agricultural insurance. Therefore, when formulating policies, the policymakers should consider regional differences and characteristics, and adopt development models keeping in view regional variations in adaptability with different agricultural insurance densities, Moreover, they should improve agricultural security policies, optimize agricultural capital allocation, promote the transformation of the agricultural economy from extensional growth to connotative growth, and further improve the agricultural productive income of rural residents.

Background: Food safety incidents have aroused widespread public health concern, causing food price risk. However, the causal paths remain largely unexplored in previous literature. This paper sets out to identify the relations of local and spatial spillovers of food safety incidents and public health concerns to food price risk in consumer markets within a setting with heterogeneous food safety risk levels. Methods: (i) Theoretically, unlike prior work, this paper decomposes food safety risks into food safety incidents (objective incident component) and public health concern (subjective concern component). This article develops a theoretical framework of causality to capture the underlying causal pathways motivated by the theories of limited attention and two-step flow of communication. (ii) Empirically, using avian influenza shocks in China’s poultry markets as natural experiments, this paper differentiates between low- and high-risk food and incidents. The article adopts dynamic spatial panel models to analyze potential nonlinearity, moderation, and mediation in the spillover of food safety risk to food price risk for a long panel of 30 provinces covering the November 2007 to November 2017 period. Results: (i) Food safety incident alone only triggers high-risk food price risk, not low-risk food price risk. (ii) Public health concern amplifies nonlinear food price risk triggered by food safety incident. (iii) High-risk incident intensifies negative pressure of public health concern on food price risk. (iv) Food safety incident indirectly affects high-risk food price risk through public health concern. Conclusions: Using a setting with heterogeneous risk levels, this paper documents that (i) food safety incident itself does not necessarily determine food price risk, whereas it is actually public health concern that directly causes nonlinear food price risk; (ii) public health concern spillover to food price risk is negatively moderated by high-risk incident, and (iii) food safety incident spillover to high-risk food price risk is mediated by public health concern. The findings complement current research by (i) elucidating the diverse impacts of food safety incident and public health concern on food price risk, which are obscure in previous literature, and (ii) highlighting that heterogeneous food and incident risk levels matter for determining food price risk spillover.

As the media have continued to pay increasing attention to pig epidemic events, some local pig epidemic events may have a large degree of negative impact on the pork market and the whole pig industry chain, leading to pork price fluctuations. Strengthening pig epidemic control, monitoring media reporting sentiment, and stabilizing pork price fluctuations are important measures to improve the economy and people’s livelihood. This paper sets out to identify the relationship between the negative media sentiment about the pig epidemic and the market risk of pork prices within a setting with pig epidemic risk. Based on the provincial panel data of China from January 2011 to December 2022, this paper uses the spatial panel Durbin model to investigate the impact of negative media sentiment about the pig epidemic on pork price fluctuations from the perspective of local and spillover effects, and further discusses the mechanism of consumer sentiment. The empirical results show that: (1) The negative media sentiment about the pig epidemic significantly exacerbates pork price fluctuations, and there is a single threshold effect, which is weakened after crossing the threshold value. (2) The negative media sentiment about the pig epidemic has a significant positive spillover effect on pork price fluctuations, showing the characteristics of “being a neighbor”. The spatial spillover effect shows a significant spatial attenuation feature and an inverted U-shaped change with the inflection point at 1400 km. (3) The effect is related to the heterogeneity of media reputation. The local aggravation effect of local media’s negative sentiment on pork price fluctuations is greater than that of central media and information network platforms. In terms of the spatial spillover effect, the negative sentiment of the information network platforms has the strongest effect on the aggravation of pork price fluctuations in neighboring regions. (4) The mechanism study finds that the negative media sentiment about the pig epidemic positively affects pork price fluctuations through the path of “consumer sentiment”. Therefore, this research recommends that the government department should strengthen the supervision of media sentiment about the pig epidemic and reasonably guide consumer sentiment to stabilize the pork market.

Animal disease is a major threat to the sustainability of the global livestock market. We explore the price risk spillover of avian influenza to the broiler market, from the perspective of public opinion. Unlike in previous work, where avian influenza is measured as a whole, we decompose an avian influenza epidemic into avian influenza outbreak and public opinion, measured by infection cases and Baidu and Google search volume. Theoretically, by introducing the theory of limited attention and two-step flow of communication, we develop an analytical framework to capture the causal mechanism of avian influenza outbreak, public opinion, and broiler price risk spillover, arguing that it is actually public opinion, not avian influenza outbreak alone, that directly causes broiler price risk. Empirically, using a long panel from China spanning from November 2004–November 2017, we examine the causal mechanism and analyse the nonlinear spatial spillover of public opinion to broiler price risk. We find that: (i) neither poultry nor human infection with avian influenza outbreak has a significant spillover to broiler price; (ii) on average, public opinion has a negative spillover to broiler price; in general, spillover of public opinion to broiler price is inverse U-shaped; (iii) on average, public opinion has a negative direct effect on local broiler price and a three times larger negative spatial spillover effect on nearby broiler price; in general, direct and spatial spillover effects are inverse U-shaped. Our research highlights the importance of studying public opinion in amplifying price risk when analysing spillover of animal disease to the global livestock market.

Background: During zoonotic disease shocks (ZDSs), zoonotic disease outbreaks (ZDOs) can induce public health scares (PHSs), causing meat price risks (MPRs). Nevertheless, spatial spillovers of zoonotic disease shocks in meat markets remain unclear. We explore how zoonotic disease outbreaks and public health scares locally and spatially spill over to meat price risks, and whether spatial spillovers of public health scares decay with distance. Methods: (i) We construct a long panel covering 30 provinces and 121 months, using highly pathogenic avian influenza (HPAI) epidemics as exogenous shocks in Chinese meat sector. (ii) We decompose zoonotic disease shocks into zoonotic disease outbreaks (objective incident) and public health scares (subjective information) and examine their spillovers to meat price risks. (iii) We identify distance-decaying spatial spillovers of public health scares, by running our dynamic SAR models 147 times, from 80 km to 3000 km with 20 km as incremental value, in a setting with risk-level heterogeneity. Results: (i) Zoonotic disease outbreaks themselves only cause local and neighboring meat price risks for high-risk meat, not for low-risk or substitute meat. (ii) Public health scares exacerbate local and neighboring meat price risks for high-risk and low-risk meat, and local meat price risks for substitute meat. (iii) Spatial spillovers of public health scares are distance-decaying and U-shaped, with four spatial attenuation boundaries, and distance turning point is shorter for high-risk meat (500 km) than for low-risk meat (800 km). Conclusions: We complement the literature by arguing that health scares induced by disease outbreaks negatively spill over to meat prices, with U-shaped distance-decaying spatial effects. This suggests low interregional spatial market integration in meat products, due to distance decay of nonstandardized information and local government control effects, across provincial boundaries. To the best of our knowledge, we are the first to document nonmonotonic distance decay of health scare effects on food prices, previously not found by the literature.