We extend the recently proposed multi-dimensional asymmetric information model to show that advantageous selection could be present in crop insurance with two types of coverage: (i) multiple perils (e.g. a multi-peril, 'all risk' policy), and (ii) a specific named peril (or set of perils). Our theoretical model suggests that certain characteristics of an insured farmer (or farm) under both types of coverage can be sources of advantageous selection. Farmers who advantageously select are more likely to purchase insurance coverage and less likely to realise a loss. A supplementary empirical analysis, based on data from the Philippine crop insurance market, illustrates how sources of advantageous selection can be identified econometrically.

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.

This article examines the moral hazard and adverse selection effects of cost‐of‐production (COP) crop insurance products. Building on existing crop insurance models of moral hazard, as well as a survey‐based data set that allows us to separately identify moral hazard from adverse selection, we find evidence that farmers insured under COP contracts spend more on chemical fertilizers and pesticides (i.e. those inputs whose costs determine the indemnity payments). However, since these same COP insured farmers are still likely to use less inputs (like effort) whose costs do not enter the indemnity payment formula, and yield depends on both types of inputs (i.e. the determinants and non‐determinants of the indemnity payments), the final moral hazard effect of COP insurance on yields is ambiguous. Our analysis also suggests that farmers who tend to spend less on chemical fertilizers and pesticides are the ones with private information on soil conditions and pest incidence. These are the types of farmers who adversely select into COP contracts that only cover weather related losses.

There have been a number of previous studies that examined the effects of yield-or revenue-based crop insurance products on input use of farmers. However, no study has specifically investigated the input use impacts of a cost-of-production (COP) crop insurance policy, even though this type of crop insurance is the predominant one used in several other countries outside of the United States (such as the Philippines and China). This article aims to theoretically and empirically examine the effect of a COP crop insurance product on farmers' chemical input use. Our theoretical model suggests that the effect of COP insurance on input use can either be positive or negative, with the resulting impact depending on the strengths of (a) the traditional moral hazard effect of insurance (i.e., an input use decreasing effect); versus (b) the marginal incentives to apply more inputs due to input levels being the main determinant for expected indemnity amounts in this type of insurance (i.e., an input use increasing effect). A survey data set from corn farmers in the Philippines is then used to empirically illustrate how a particular COP insurance product influences input use in a real-life context. In this case, we find that COP insurance increases the use of chemical inputs (e.g., fertilizers and total chemical expenditure), implying that the positive marginal incentive to apply more inputs dominates the negative moral hazard effect. tain types of insurance, met the criteria for exemption from WTO disciplines (see Matthews (2018) at http://capreform.eu/recent-trends-in-euwto-domestic-support-notifications/). 2 For example, subsidies to the US federal crop insurance program have been increased over the years to reach high target program participation levels (See Shields (2015) at https://nationalaglawcenter.org/wp-content/ uploads/assets/crs/R43951.pdf).