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Federally subsidized crop insurance aims to mitigate farm risks of crop producers. A body of literature has examined informational problems under this program. However, few studies empirically link crop insurance participation with farm financial performance. Most use county-level aggregates to argue that crop insurance participation is associated with increased farm financial debt. Using farm-level data, this study provides empirical evidence of crop insurance's effects on farm financial risk.

The impact of crop insurance on farm financial risks is assessed using farm-level data from Kansas. The sample consists of at least 1,600 farms each year from 2002 to 2015. Financial risks are measured using the probability of falling into the critical zone of five different financial ratios. The study uses two matching estimators to estimate the causal effects of crop insurance participation on farm financial risks. Several alternative empirical approaches account for unobserved heterogeneity and potential endogeneity.

Crop insurance participation has reduced the farm's likelihood of being in the critical liquidity risk by 8%. This result is robust across matching estimators and alternative specifications to account for unobserved heterogeneity and potential endogeneity.

This is one of the few studies to examine whether crop insurance reduces farm financial risks. This study provides empirical evidence of the extent to which crop insurance enrollment impacts farm financial risks. Findings suggest that crop insurance is critical to maintaining the financial well-being of crop producers, and significantly reduces the likelihood of producers being in a critical liquidity risk.

This paper presents the systematic process framework to develop the suitable crop insurance for each agriculture farming region which has individual differences of associated crop, climate condition, including applicable technology to be implemented in crop insurance practice. This paper also studies the adoption of new insurance scheme to assess the willingness to join crop insurance program.

Crop insurance development has been performed through IDDI conceptual framework to illustrate the specific crop insurance diagram. Area-yield insurance as a type of index-based insurance advantages on reducing basis risk, adverse selection and moral hazard. This paper therefore aims to develop area-yield crop insurance, at a provincial level, focusing on rice insurance scheme for the protection of flood. The diagram demonstrates the structure of area-yield rice insurance associates with selected machine learning algorithm to evaluate indemnity payment and premium assessment applicable for Jasmine 105 rice farming in Ubon Ratchathani province. Technology acceptance model (TAM) is used for new insurance adoption testing.

The framework produces the visibly informative structure of crop insurance. Random Forest is the algorithm that gives high accuracy for specific collected data for rice farming in Ubon Ratchathani province to evaluate the rice production to calculate an indemnity payment. TAM shows that the level of adoption is high.

This paper originates the framework to generate the viable crop insurance that suitable to individual farming and contributes the idea of technology implementation in the new service of crop insurance scheme.

This article analyzes farmers' preferences for different nonindexed crop insurance alternatives, using discrete choice experiment data on cocoa farmers from southern Ghana. We examine farmers' attendance to attributes by comparing self-reported attribute nonattendance (ANA) to the behavior inferred from the choices.

We utilize the latent class endogenous attribute attendance (EAA) model to address potential endogeneity by jointly modelling farmers' attribute processing strategies with their choice of attributes of the insurance products.

The results show that premium levels, mode and length of indemnity payouts tend to influence farmers' preferences for crop insurance products. The findings also reveal that credit-constrained farmers attend more to premium and payment mode attributes of the crop insurance products and that credit-constrained farmers tend to exhibit lower willingness-to-pay estimates for the crop insurance attributes.

The findings from the study suggest that credit constraints do not only limit input use, but also tend to have statistically significant impact on farmers' cocoa insurance participation decisions.

The study examines the impact of credit constraints on farmers' crop insurance preferences while accounting for ANA.

This study seeks to evaluate the impacts of land rental arrangements on crop insurance and grain marketing decisions.

The analysis is conducted in an Illinois corn‐soybean setting in which optimal marketing and crop insurance decisions are estimated for a risk‐averse producer under typical cash rent and share rent agreements using numerical simulation methods.

Results indicate that the availability of crop insurance impacts the intensity of use of put options under both cash and share rent arrangements. Similar to previous work in this area, revenue insurance is found to cause a substitution away from marketing using put options, while yield insurance is complementary to price risk management alternatives. However, while insurance and marketing play a role under both types of land tenure arrangements, shifting from a cash rent to a share rent agreement provides a relatively greater degree of risk reduction.

The results suggest that additional research is needed to explain trends in land rental contracts. Crop insurance and other federal programs may provide incentives to switch from share leases to cash rent arrangements. Changes to the design of these programs could facilitate risk management for producers more efficiently.

The unique contribution of this study is the comparison of insurance and marketing decisions under both cash rent and share rent agreements for crop land.

The purpose of this paper is to examine the reduction of crop yield uncertainty using rainfall index insurances. The insurance payouts are determined by a transparent rainfall index rather than actual crop yield of any producer, thereby circumventing problems of adverse selection and moral hazard. The authors consider insurances on rainfall indexes of various months and derive an optimal insurance portfolio that minimizes the income variance for a crop producer.

Various regression models are considered to relate crop yield to monthly mean temperature and monthly cumulative precipitation. A bootstrapping method is used to simulate weather indexes and corn yield in a future year with the correlation between precipitation and temperature incorporated. Based on the simulated scenarios, the optimal insurance portfolio that minimizes the income variance for a crop producer is obtained. In addition, the impact of correlation between temperature and precipitation, availability of temperature index insurance and geographical basis risk on the effectiveness of rainfall index insurance is examined.

The authors illustrate the approach with the corn yield in Illinois east crop reporting district and weather data of a city in the same district. The analysis shows that corn yield in this district is negatively influenced by excessive precipitation in May and drought in June–August. Rainfall index insurance portfolio can reduce the income variance by up to 51.84 percent. Failing to incorporate the correlation between temperature and precipitation decreases variance reduction by 11.6 percent. The presence of geographical basis risk decreases variance reduction by a striking 24.11 percent. Allowing for the purchase of both rainfall and temperature index insurances increases variance reduction by 13.67 percent.

By including precipitation shortfall into explanatory variables, the extended crop yield model explains more fluctuation in crop yield than existing models. The authors use a bootstrapping method instead of complex parametric models to simulate weather indexes and crop yield for a future year and assess the effectiveness of rainfall index insurance. The optimal insurance portfolio obtained provides insights on the practical development of rainfall insurance for corn producers, from the selection of triggering index to the demand of the insurance.

The purpose of this paper is to demonstrate how crop price insurance premium can be calculated using an option pricing model and how insurers can transfer underwriting risks in the futures market.

Based on data from spot and futures market in China, this paper develops an improved B-S model for the calculation of crop price insurance premium and tests the possibility of hedging underwriting risks by insurance firms in the futures market.

The authors find that spot price of crops in China can be estimated with agricultural commodity futures prices, and can be taken as the insured price for crop price insurance. The authors also find that improved B-S model yields better estimation of crop price insurance premium than traditional B-S model when spot price does not follow geometric Brownian motion. Finally, the authors find that hedging can be one good alternative for insurance firms to manage underwriting risks.

This paper develops an improved B-S model that is data-driven in nature. Insured price of the crop price insurance, or the exercise price used in the B-S model, is estimated from a co-integration model built on spot and futures market price series. Meanwhile, distributional patterns of spot price series, one important factor determining the applicability of B-S model, is factored into the improved B-S model so that the latter is more robust and friendly to data with varied distributions. This paper also verifies the possibility of hedging of underwriting risks by insurance firms in the futures market.

The USDA’s Risk Management Agency (RMA) made several changes to the crop insurance products available to organic growers for the 2014 crop year. Most notably, a 5 percent premium surcharge was removed and organic-specific transitional yields (t-yields) were issued for the first time. The purpose of this paper is to use farm-level organic crop yield data to analyze the impact of these reforms on producer insurance outcomes and compare the insurance options for new organic growers.

This study uses a unique panel data set of organic corn and soybean yields to analyze the impact of organic crop insurance reforms. Actual Production History values and premium rates are calculated for each farm and crop yield sequence. Producer loss ratios and subsidized premium wedges are compared for yield, revenue and area-risk products before and after the instituted reforms.

Results indicate that RMA succeeded in improving the actuarial soundness of the organic insurance program, though further refinement of organic t-yields may be necessary to accurately reflect the yield potential of organic producers and avoid reductions in program participation.

This paper provides insight into the effectiveness of reforms intended to improve the actuarial soundness of organic crop insurance and demonstrates the effect that the reforms are likely to have on new and existing organic farms. Because this analysis uses data collected independently of RMA and includes farms that may or may not have purchased crop insurance, it avoids the self-selection problems that might affect analyses using crop insurance program data.

In Nepal, crop insurance is at initial phase. However, since its implementation seven years ago, the adoption rate has been fairly low even with the government's lucrative subsidy on premium. There have been very limited studies on specifics of insurance for different crops, and farmer's acceptability on insurance. This study examines WTP for tree-based insurance, a potential insurance scheme on fruit crops in hilly areas of Nepal.

The authors used a contingent valuation method to estimate farmer's willingness to pay (WTP) premium for insurance. They used a double-bounded dichotomous choice (DBDC) framework to elicit WTP and an interval regression method to estimate the WTP model.

The authors found that the farmers revealed WTP for tree-based insurance is three times higher than the premium they would pay under government's current subsidy plans of insurance. The authors’ result from interval regression also suggests that the factors such as farm size, farmer's adverse experience about invasive pest and weather, awareness of crop insurance, farming experience, and family involvement in agriculture significantly influence farmers' WTP.

A distinct modality of insurance, like tree-based insurance for fruit crops in mid and high hill areas, may enhance the adoption rate rather than a broad area-based plan generalized for all crops.

Only a few studies have examined specifics of insurance in fruit crop insurance in developing countries. The authors’ estimated WTP factors influencing WTP on citrus fruit-crop insurance in Nepal indicates that there is a scope for extending this insurance program. However, the authors also found that there is a gap in understanding of crop insurance and have limited awareness on the government's subsidy programs among farmers.

The purpose of this paper is to assess farmers’ willingness to participate and pay for weather-based index insurance in the Upper East Region of Ghana, and what factors influence the participation and purchase of crop insurance schemes.

A survey of 200 farmers in the region was carried out in 2018 to measure demographic information, farm characteristics, risks and risk-management practices and attitudes to crop insurance programs. The survey also captured maximum willingness to pay (WTP) for crop insurance. The double-bounded contingent valuation technique was used to estimate the WTP for crop insurance and the variables that affected WTP.

Farmers, in general, had an indifferent attitude to crop insurance in the region, but were willing to participate in the crop insurance programme, and were willing to pay between 7.5 and 12.5 per cent of the cost of growing maize as a premium for crop insurance. Demographic and economic variables did not impact WTP, but attitude towards crop insurance, farm diversification and frequency of drought negatively impacted on the WTP for crop insurance.

Education programs could be undertaken to improve the attitude and understanding towards crop insurance, as some farmers perceived the programme as not trustworthy, and others did not truly understand the operation of the programme.

Drought can have a significant impact on household welfare, particularly in food insecure countries or regions. Crop insurance can provide a method of securing income for farmers allowing them to purchase food rather than other choices, such as removing children from education to reduce household expenses, improving the long-term welfare of the farm household.

This paper considers willingness to participate and WTP for a crop insurance programme in Ghana, it is one of a small number of papers that consider attitude to, and willingness to participate and WTP for crop insurance in developing countries. The value of the research is the expanded understanding of farmer attitude to crop insurance and their lack of knowledge of crop insurance operations.

Since 1980, the principal form of crop loss assistance in the United States has been provided through the Federal Crop Insurance Program. The Federal Crop Insurance Act of 1980 was intended to replace disaster programs with a subsidized insurance program that farmers could depend on in the event of crop losses. Crop insurance was seen as preferable to disaster assistance because it was less costly and hence could be provided to more producers, was less likely to encourage moral hazard, and less likely to encourage producers to plant crops on marginal lands. Despite substantial growth in the program, the crop insurance program has failed to replace other disaster programs as the sole form of assistance. Over the past 20 years, producers received an estimated $15 billion in supplemental disaster payments in addition to $22 billion in crop insurance indemnities.