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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.

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.

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.

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 examines the effect of overconfident yield forecasting (optimism bias) on crop insurance coverage level choices across both yield and revenue insurance.

This study simulates a representative producer’s preferred coverage level for both yield and revenue insurance under three potential models of decision-making and four potential manifestations of overconfident yield forecasting. The study then uses this framework to examine how coverage level choices change as overconfidence increases (decreases).

As overconfidence increases, producers prefer lower levels of crop insurance coverage than they would otherwise prefer, with extreme overconfidence inducing farmers to buy no insurance at all. While overconfidence affects cross-coverage demand for revenue and yield insurance similarly, this effect is more pronounced for yield insurance. Cross-coverage level demand for revenue insurance is relatively stable across changes in the correlation between prices and yields.

This research has important implications for crop insurance subsidy design and crop insurance demand modeling.

There is a growing body of literature suggesting that producers are overconfident with regard to their future yield risk and that this bias reduces their willingness to pay for risk management tools such as crop insurance. This is the first study to look at how such overconfidence affects cross-coverage level demand for crop insurance.

The purpose of this study is to establish household‐level food security risks associated with climate variation, and how households respond to these risks in a patriarchal society such as in Northern Cameroon where subsistence women producers have less control over resources required to support the food production sector which depends entirely on the quality of the rainy season.

Primary data from 116 female‐headed households (FHHs) and 184 male‐headed households (MHHs) is examined for the three Northern provinces of Cameroon. The survey generated information on the response and coping strategies to climatic variation; and the socioeconomic impacts of climate on households. The multinomial logit model is employed to establish the determinants of the choice selection for climate risk coping options by households.

Both FHHs and MHHs are exposed to stresses related to food production and availability, low incomes and food accessibility and utilization of food supplies, heightened by the real and perceived effects of the variability of current climate. Short‐term coping choices include diversification of livelihood which in turn impacts food accessibility and consumption choices.

A seasonal pattern is revealed in household expenditure with households spending more than 70 percent of their income on food in spring. The lowest food expenditures are in summer. Market and income manipulation choices for food supply stability include a range of non‐farm income generation strategies to cope with expected shortages induced by climatic variability. The current climate variation, household demography, and farming conditions via access to credit, tenure, and extension service delivery are significant determinants of coping choices for households perceiving change in climatic patterns.

Significant seasonal patterns in household food availability, accessibility and utilization are observed with important implications for both household welfare and as precursor to long‐term adaptation to climate change.

This paper examines the relationship between farm-level variables related to cash flow and premium rates on federal crop insurance coverage selection.

Using farm-level data from the Agricultural Resource Management Survey (ARMS), the authors estimate a linear fixed effects model to evaluate the relationship between farm-level and regional variables and federal crop insurance coverage selections.

The authors find evidence indicating that expected cash flow plays an important role in coverage level decisions. For example, variables directly related to cash flow, such as higher costs, are associated with significant differences in coverage level selection, though the direction of the association is dependent on the type of costs, whether fixed or variable, while higher revenue higher acreage farms insure at higher coverage levels. In addition, higher premium costs are associated with lower coverage level selections, despite subsidy incentives.

This is the first paper that identifies a potential solution to the puzzling finding that farmers do not consistently maximize coverage level. This research points to the influence of credit constraints as playing a role in limiting coverage level selections.

The purpose of this paper is to examine the spatial components of producer heterogeneity in crop insurance product selection among US corn producers and identifies neighborhood spillover or agent marketing effects in these decisions.

County‐level insurance and yield data are used to demonstrate that a gradual shift from yield‐based insurance to revenue‐based insurance has spatial patterns. Conventional risk variables such as yield variability, price variability, prevalence of irrigation, other crops, and yield‐price relationships play an important role in this shift and are consistently estimated only when spatial components are included. A spatial random effects model is used to also identify the impact of spatial lag effects, which include neighborhood spillover and agent marketing effects, on the share of corn acres insured with revenue‐based plans vs yield‐based plans.

Theoretically consistent variables associated with risk are found to significantly influence the choice between crop revenue and yield insurance. Non‐linear parameters identify the region‐specific effects from changes in irrigation, yield price correlation, and the prevalence of corn production on insurance decisions. In addition, spatial components such as the decisions made by nearby producers and marketing drives are also found to influence decisions. These results may demonstrate the relative influence of trusted sources, such as nearby producers and insurance agents, on insurance decisions.

Traditional risk variables are consistently estimated by controlling for spatial heterogeneity. This study also reveals the propensity of producers to rely on the opinions of other producers or agents that they know.

This study analyzes the impact of COVID-19 on agricultural production in South India by evaluating the influence of market channels and socioeconomic conditions on the production decisions of farmers during two key cropping seasons. We base our analysis on primary data from 200 marginal, small and medium farmers, primarily focusing on the key seasonal crops, namely paddy and black gram.

We studied the downstream supply chains of paddy and black gram crops in the district of Villupuram, situated in the South Indian state of Tamil Nadu. Using a Bi-Probit model, we analyzed the production decisions of marginal, small and medium farmers engaged in paddy and black gram cultivation. Various factors are considered, including farmers’ socioeconomic characteristics, gender, market channels accessed and the coping strategies employed.

After the easing of lockdown measures in June 2020, our research revealed substantial disruptions in agricultural production during the critical Kharif and Rabi seasons. Most farmers refrained from returning to their fields during the Kharif season; those who did produced millet as the main crop. Factors such as choice of market channels in previous seasons, economic status, access to all-weather roads, labor availability, gender and coping strategies played an important role in the return to production in the subsequent Kharif and Rabi seasons.

Our data revealed several interesting threads related to price volatility, irrigation and access to markets and their impact on food security. The role of intermediaries and market channels in providing liquidity emerges as an important aspect of farmers' choice of markets. The pandemic impacted all these factors, but a detailed analysis was beyond the scope of this study.

We also find that resilience to economic shocks varies not only by economic status but also by gender and social groups. Farmers with female members are more likely to be resilient, and marginal and small farmers primarily belong to social groups that are economically less developed.

This study contributes to the literature on factors influencing farmer choice and decision-making and provides nuances to discussions by analyzing crop-specific supply chains, highlighting the critical role of socioeconomic factors. It also highlights the role of demographics and infrastructural factors like access to all-weather roads and access to markets that influence farmers’ production decisions.

The purpose of this paper is to evaluate the Dual Use (DU) Option – a crop insurance policy created by the 2018 Farm Bill – relative to other policies available to dual-purpose annual forage producers. The new policy combines existing rainfall-based policies for annual forage crops and multi-peril policies for grain, allowing coverage for multiple crop uses on the same acres during the same growing season.

The paper uses a simulation model to examine crop insurance choices for a typical Texas dual-purpose wheat farm. The certainty equivalent (CE) of wealth is used to rank choices within and between three insurance plans and to analyze the effects of those choices over a range of producer risk aversion levels and for three cases of yield expectations.

The DU Option is more preferred as risk aversion increases, but it is not universally preferred. Therefore, while the policy can be a viable risk management tool, certain restrictions may be limiting its effectiveness.

The findings of this paper can help explain farm-level decision making related to dual-purpose annual forage crop insurance program choices.

This paper contributes to the literature by documenting a new crop insurance program made available in the 2018 Farm Bill and provides insights into producers' possible choices by evaluating extensive scenarios.