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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.

The aim of this paper is to identify the factors that influence rice farmers' decisions to adopt crop insurance and premium payments (willingness to pay [WTP] amounts). The paper also demonstrates the usefulness of the complementary log-log (cloglog) truncated Poisson double-hurdle model as an alternative hurdle model.

The study first investigated the nature of the dependent variable, which had non-normal residuals and was overdispersed. The probit truncated normal regression double-hurdle model was tried but it failed the normality and homoscedasticity tests; hence, the cloglog truncated Poisson double-hurdle model was employed in the study.

An estimated 61% of respondents would purchase crop insurance, despite farmers not having prior experience with this product. Amongst others, the factors that influence insurance adoption amongst rice farmers are the share of rice in total income, reliability perception of crop insurance schemes and the probability of failure to achieve target yields. The latter helps the authors to address adverse selection, a central issue to the viability of such an insurance programme. The determinants of farmers' WTP are also identified.

Sampling was limited to farmers using irrigation and living in one region of Ghana, which may limit the study’s wider applicability.

As far as the authors are aware, this study is the first to select the appropriate hurdle model based on established properties of the dependent variable on this topic – crop insurance decisions.

Agricultural and fishery disasters are rather obscure emergency management research topics. However, the Food and Agriculture Sector is one of only 16 critical infrastructure sectors included in the Robert T. Stafford Disaster Relief and Emergency Assistance Act of 1988, and the sector is a vital component of the United States economy. As climate change continues to increase the frequency and severity of agricultural and fishery disasters, the Food and Agricultural Sector must adapt to and cope with unprecedented levels of risk. This chapter provides an overview of federal agricultural and fishery disaster policy and explores whether such policies are consistent with Jerroleman’s (2019)principles of just recovery.

Regional differences in crop insurance uptake have persisted over time. To partly explain this phenomenon, the purpose of this paper is to propose and evaluate a budget constraint (heuristic) effect within the standard expected utility theory (EUT) framework through simulation methods.

Within the EUT framework, a standard simulation model is used to gain insights into farm insurance decisions when a budget constraint is in effect. The budget constraint is modeled as it has been revealed through the data on farmers’ insurance expenditures. In the simulation analysis, certainty equivalent values are used to rank farm options subject to the revealed budget constraint.

A budget constraint effect within the EUT framework stands out in explaining the observed regional differences. The proposed explanation is consistent with the historical trends on the ratio of crop insurance expenditure to expected crop value, higher premium rates in regions with lower crop insurance uptake, and the limited turnout for the 2014 Farm Bill’s supplemental area-based crop insurance products. Farmers’ crop insurance choices are found to be mostly constrained-optimal.

This appears to be the first study taking the revealed preferences approach to farmers’ crop insurance choices in a simulation analysis. Some policy implications are drawn and future research avenues are suggested. The findings should be of considerable value to policymakers, academics, bankers, and producers in regard to the design and use of risk management tools.

The purpose of this paper is to analyze the optimal reinsurance contract structure from the crop insurer's perspective.

A very powerful and flexible empirical‐based reinsurance model is used to analyze the optimal form of the reinsurance treaty. The reinsurance model is calibrated to unique data sets, including private reinsurance experience for Manitoba, and loss cost ratio (LCR) experience for all of Canada, under the assumption of the standard deviation premium principle and conditional tail expectation risk measure.

The Vasicek distribution is found to provide the best statistical fit for the Canadian LCR data, and the empirical reinsurance model stipulates that a layer reinsurance contract structure is optimal, which is consistent with market practice.

While the empirical reinsurance model is able to reproduce the optimal shape of the reinsurance treaty, the model produces some inconsistencies between the implied and observed attachment points. Future research will continue to explore the reinsurance model that will best recover the observed market practice.

Private reinsurance premiums can account for a significant portion of a crop insurer's budget, therefore, this study should be useful for crop insurance companies to achieve efficiencies and improve their risk management.

To the best of the authors' knowledge, this is the first paper to show how a crop insurance firm can optimally select a reinsurance contract structure that minimizes its total risk exposure, considering the total losses retained by the insurer, as well as the reinsurance premium paid to private reinsurers.

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.

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.

The purpose of this paper is to contribute to the aforementioned literature on the linkage between economic activity and human preference by estimating the cross-sectional determinants of farmers’ participation in participation in crop insurance programs (CIPs) and identifying the impediments preventing the remaining farmers from participating.

Using the unique data sets of risk preference experiments and maize producer surveys pertaining to the maize production areas of China, this paper explores the determinants of farmers’ CIPs and scrutinizes the role of risk aversion in farmers’ CIP purchase decisions under the expected utility maximization framework. And a “non-zero threshold probit model” is used for the analysis.

The results show that risk aversion plays an important role in CIP purchase decision-making, not only in the form of its direct effect but also with regard to the interaction term and expected loss. Furthermore, if the insured amount is high enough, then risk aversion will no longer affect insurance purchase. Additionally, purchase experience, CIP environment (village purchase ratio), and contract items (insured amounts) are significant determinates in these decisions. There is no significant evidence to suggest that serious adverse selection exists in the sampling areas.

One theoretical model is established which considered not only general variables like farmers’ production and household information, but also conditions and terms in the insurance policies. The unique experimental method is used to measure farmers’ risk aversion. Both the role of risk aversion and its’ interaction terms with others in CIP participation are scrutinized to identify complicated influences under the context of real society.

Agriculture insurance is the panacea for the farming community. Many policy interventions were implemented for stimulating agriculture insurance access to farmers in India. However, access to agriculture insurance constantly remained one of the major challenges to Indian policy planners. The goal of the present paper is to explore current policy interventions in the area of agriculture insurance in India.

The present paper reviews and analyzes the evidence literature through a content analysis method on development and performance analysis perspective of existing agriculture insurance schemes in India.

Agriculture insurance is a significant risk management policy, but this is not easily reachable to the majority of farmers in India. The government of India introduces a novel agriculture scheme every decade, but every crop insurance scheme was inconsistent and ineffective owing to operational defects. Agriculture insurance in India is still developing in terms of coverage, scope, and exposure, but farmers' dissatisfaction about agriculture insurance turned out to be a negative word of mouth. Insurance illiteracy and farmers' preference for agriculture relief payments are the main reasons for limited access to agriculture insurance. The current crop insurance schemes are improperly operated because of implementation issues at the state level.

This paper will be useful for researchers and academicians to analyze the past and present status of crop insurance in India.

The paper is the unique work of the authors as it has attempted to present India's journey with agriculture insurance. An effort is made in the present study to provide a comprehensive and holistic developmental and performance analysis perspective of agriculture insurance in India.

The purpose of this paper is to investigate the role of crop insurance among Hungarian crop farmers and the responses to the introduction of the two-scheme risk management system. Specifically, first, it examines the economic and environmental factors affecting the willingness of farmers to contract crop insurance. Second, it reveals the relationship between having crop insurance and technical efficiency of crop producing farms.

Probit models of panel data are applied to explore the factors of insurance decisions. The relationship between efficiency and insurance is investigated with two-stage data envelopment analysis (DEA) model with double bootstrap using panel data for the 2001 to 2014 period.

The results of Probit model estimations show that the education, the size, the indebtedness of crop producing farms and the new two-scheme risk management system are in positive correlation, while the concentration of farming activity are in negative correlation with the crop insurance contracting. The estimations of two-stage DEA model reveal that crop producing farms with an agricultural insurance contract are more efficient than the farmers without using this risk management tool.

Empirical investigation of the influencing factors of agricultural insurance demand in Hungary and the examination of the relationship between insurance and technical efficiency may contribute to the development of Hungarian risk management system.