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The purpose of this paper is to explain the factors affecting crop insurance purchases by farmers in Inner Mongolia, China.

A survey of farmers in Inner Mongolia, China, is undertaken. Selected variables are used to explain crop insurance purchases, and a probit regression model is used for the analysis.

Results show that a number of variables explain crop insurance purchases by farmers in Inner Mongolia. Of the eight variables in the model, seven are statistically significant. The eight variables used to explain crop insurance purchases are: knowledge of crop insurance, previous purchases of crop insurance, trust of the crop insurance company, amount of risk taken on by the farmer, importance of low crop insurance premium, government as the main information source for crop insurance, role of head of village, and number of family members working in the city.

A possible limitation of the study is that data includes only one geographic area, Inner Mongolia, China, and so results may not always fully generalize to all regions of China, for all situations.

Crop insurance has been recently expanded in China, and the information from this study should be useful for insurance companies and government policy makers that are attempting to increase the adoption rate of crop insurance in China.

Crop insurance may be a useful approach for stabilizing the agricultural sector, and for increasing agricultural production and food security in China.

This is the first study to quantitatively model the factors affecting crop insurance purchases by farmers in Inner Mongolia, China.

Constrained input use and lower productivity of rural establishments may be associated with restricted or concentrated access to financial resources, especially in developing countries. Meanwhile, agricultural activity entails risks associated with the volatility of net cash flows and external events, which may discourage riskier but higher return investments (e.g. technology). As rural credit can alleviate the former, and rural insurance may help alleviate the latter, the combination of both policies might endorse each other. The purpose of this study is to analyze the use of rural credit and rural insurance policies with respect to productivity and crop area, in São Paulo state, Brazil, using farmer's microdata from two surveys realized in 2007/08 and 2016/17.

This study uses propensity score matching and the entropy balance approaches in a complementary way. This study compared three policy treatments – rural credit, rural insurance and both policies combined, against establishments that received neither one. The analysis considered sugarcane, grain and grape crops separately and employed farmer's microdata. Moreover, the analysis was stratified into two categories: establishments owned by family farmers and those that did not.

Rural credit policy is related to higher productivity and larger cultivated area for grains and only to larger area for grape crops in the last analyzed period (2016/17). Rural insurance, as a unique policy or combined with credit, is related to higher productivity and cultivated areas, for all analyzed crops, only in the second period (2016/17), as the policy became more accessible to farmers. Heterogeneity regarding crops and farmers might influence the effectiveness of these policies. Despite rural insurance being related to a better performance regarding the outcome variables, it still reaches a small share of farmers, especially when combined with credit.

Many studies about the effectiveness of rural credit in Brazil have been conducted throughout the years, while there have been fewer studies regarding rural insurance since it became an important policy in the mid-2000s. However, few studies have conducted an analysis comparing its individual and interactive influences, with such level of disaggregation, on a farm-level database, considering the heterogeneity of the data and the different categories of farmers.

The purpose of this paper is to identify the correlates of crop insurance adoption and estimate the impact on debt and farm income.

The authors used nationally representative data from National Sample Survey Office (NSSO), which consisted of 35,200 farming households. Logit and propensity score matching (PSM) (nearest neighbor, caliper and kernel matching) techniques were used.

With only around 5% of households insuring their crops and 87% of them not receiving claims, crop insurance in India has failed. Logit model estimates of correlates of adoption indicated that households with larger family size, lower social group, less education, lower standard of living and poor were more likely to be left out of the ambit of crop insurance. Further, propensity score estimates suggested that households with access to crop insurance had significantly lesser outstanding debt with positive effect on input costs and crop income. The authors’ results were in contrast to the risk balancing theory.

Results of our work encourage us to rethink and restructure the crop insurance policy design in India. With credit and insurance markets interlinked by design and as the risk balancing in the farm business found absent, policies to strengthen both the markets are the need of the hour. To encourage more farmers to take up crop insurance, revenue-based indemnity calculation could be tried in India.

Impact estimates from three different algorithms of matching were compared and tested for robustness. Consistent average treatment effect on treated (ATT) was considered for interpretation and policy implications. Since the data are from a nationally representative survey, results are believed to be of extreme value to policy makers and insurance providers as it can be generalized.

The purpose of this paper is to use simulation analysis to assess farmer choice between crop insurance and supplemental revenue options as proposed during development of the Agricultural Act of 2014.

The certainty equivalent of wealth is used to rank farm choices and assess the effects of supplemental revenue options on the crop insurance plan and coverage level chosen by the producer under a range of farm attributes. The risk-reducing effectiveness of the select programs is also examined through their impact on the farm revenue distribution. The dependence structure of yield and prices is modeled by applying copula techniques on historical data.

Farm program supplemental revenue programs generally have no effect on crop insurance choices. Crop insurance supplemental revenue programs typically reduce crop insurance coverage at high coverage levels. An individual plan of crop insurance combined with a supplemental revenue insurance plan may substitute for incumbent area crop insurance plans.

The analysis provides insights into farmers’ possible choices by focussing on alternative crops and farm attributes and extensive scenarios, using current data, crop insurance plans and programs contained in the 2014 Farm Bill and related bills. The results should be of value to policy officials and producers in regards to the design and use of risk management tools.

The crop insurance purchase decision for a group of Kansas farmers is analyzed using farm‐level data from the 1990s, a period that experienced many changes in the federal crop insurance program. Results indicate a reduction in the elasticity of the demand for crop insurance with respect to premium rates by the end of the decade. The reduction in demand elasticity corresponded with a considerable increase in government subsidies by the end of the 1990s. This result may also reflect the attractiveness of new revenue insurance products which may have made producers less sensitive to premium changes.

An economic analysis is presented of the Standard Reinsurance Agreement (SRA), the contract governing the relationship between the Federal Crop Insurance Corporation and the private insurance companies that deliver crop insurance products to farmers. The paper outlines provisions of the SRA and describes the modeling methodology behind the SRA simulator, a computer program developed to assist crop insurers and policy makers in assessing the economic impact of the Agreement. The simulator is then used to analyze how the SRA affects returns from underwriting crop insurance. The results are presented in aggregate and also at the regional and individual company levels.

The Agriculture Improvement Act of 2018 directed the United States Department of Agriculture (USDA) Risk Management Association to investigate a policy targeted to farms and ranches that sell through local food markets. However, there is no available research that quantitatively documents the extent to which local food producers utilize Federal crop insurance.

The authors utilize 2013–2016 USDA Agricultural Resource Management Survey data to compare farms and ranches with sales through local food markets to those with and without Federal crop insurance expenditure, as well as the distribution of Federal crop expenditure, across market channels and scales.

There is a little variation in Federal crop insurance expenditure across market channels, defined as direct-to-consumer only sales, intermediated sales, and a combination of direct-to-consumer and intermediated sales. Rather, the results show that scale is the primary predictor of Federal crop insurance expenditure; larger operations are more likely to have nonzero Federal crop insurance expenses.

This article provides the first national research to document descriptive statistics of the utilization of Federal crop insurance by US farms and ranches that utilize local food market channels.

This paper is based on a crop insurance implementation currently undergoing in Haiti. The purpose of this paper is to present the development of a program tailored to rice production in the Artibonite Valley, the challenges and opportunities that are arising from the exercise as well as pitfalls and ways to avoid them.

The Système de Financement et d’Assurances Agricoles en Haïti’s approach for the development of crop insurance is in accordance with 13 concepts considered essential in the implementation of agricultural insurance programs. The case study is presented through each of these 13 fundamental concepts.

The paper provides an insight on challenges any organization will face when implementing crop insurance for smallholder farmers. It points out notably that close collaboration of executing agencies with local partners is essential from data collection through insurance development and delivery and that all participants should receive a specific training tailored to their level of education and understanding.

Haiti is one of the poorest countries on the planet. Smallholder farmers could benefit a lot from crop insurance. It could help them stabilize their income when facing crop losses due to natural hazards or uncontrollable natural events.

This paper fulfills an identified need to share real case studies exposing challenges faced when implementing crop insurance for smallholder farmers.

This research examines factors influencing the adoption of crop and revenue insurance. This is accomplished by estimating a multinomial logit model of insurance choices facing U.S. farmers. Results indicate significant differences in the probabilities of adoption of each insurance plan. The levels of selected explanatory variables, such as operator’s education level, debt‐to‐asset ratio, off‐farm income, soil productivity, participation in production and marketing contracts, and type of farm ownership, appear to be the determinants of the probability of having adopted each insurance plan.

Despite the susceptibility of cotton crops to pest attacks in the Malwa Region of Indian Punjab, no crop insurance policy has been implemented there– not even the Pradhan Mantri Fasal Bima Yojana (PMFBY), which is a central scheme. Therefore, this paper attempts to gauge the likely impact of the PMFBY on Punjab cotton farmers and assess the changes needed for greater uptake and effectiveness of PMFBY.

The authors have conducted a primary survey to conduct this study. Initially, the authors compared the costs of cotton production with the returns in two scenarios (with and without insurance). Additionally, the authors have applied a logistic regression framework to examine the determinants of the willingness of farmers to participate in the crop insurance market.

The study finds that net returns of cotton crops are conventionally small and insufficient to cope with damages from crop failure. Yet, PMFBY will require some modifications in the premium rate and the level of indemnity for its greater uptake among Punjab cotton farmers. Additionally, using the logistic regression framework, the authors find that an increase in awareness about crop insurance and farmers' perceptions about their crop failure in the near future reduces the willingness of the farmers to participate in the crop insurance markets.

The present study looks for the viability of PMFBY in Indian Punjab for the cotton crop, which can also be extended to other crops.

Punjab could also use crop insurance to encourage diversification in agriculture. There is a need for special packages for diversified crops under any crop insurance policy. Crops susceptible to volatility due to climate-related factors should be identified and provided with a special insurance package.

There exist very scant studies that have discussed the viability of a central crop insurance scheme in the agricultural-rich state of India, i.e. Punjab. Moreover, they do not also focus on crop losses accruing due to pest and insect attacks.