Tailored to the extremes: Quantile regression for index‐based insurance contract design

A new approach for weather index‐based insurance design based on Quantile Regression (QR) to condition the yield‐index dependency is developed and compared to standard regression technique. Three conceptual different risk measures, i.e., Expected Utility, Expected Shortfall and a Spectral Risk Measure, are used to evaluate the risk reducing properties of these contracts. Our findings show that QR is much more powerful in establishing the yield‐index dependency and lead for all risk measures to a higher risk reduction than the standard technique ordinary least squares (OLS). Thus, QR leads to a more efficient contract design, which is beneficial for both, the insurer (smaller remaining risk) and the insured (higher demand and willingness to pay). Our empirical application is based on a 31 years long time series of wheat yield data from Northern Kazakhstan.     

Managing basis risk with multiscale index insurance

Agricultural index insurance indemnifies a farmer against losses based on an index that is correlated with, but not identical to, her or his individual outcomes. In practice, the level of correlation may be modest, exposing insured farmers to residual, basis risk. In this article, we study the impact of basis risk on the demand for index insurance under risk and compound risk aversion. We simulate the impact of basis risk on the demand for index insurance by Malian cotton farmers using data from field experiments that reveal the distributions of risk and compound risk aversion. The analysis shows that compound risk aversion depresses demand for a conventional index insurance contract some 13 percentage points below what would be predicted based on risk aversion alone. We then analyze an innovative multiscale index insurance contract that reduces basis risk relative to conventional, single‐scale index insurance contract. Simulations indicate that demand for this multiscale contract would be some 40% higher than the demand for an equivalently priced conventional contract in the population of Malian cotton farmers. Finally, we report and discuss the actual uptake of a multiscale contract introduced in Mali.     

Crop insurance policies and purchases in France

While many crop insurance systems have been reformed around the world, few academic researches have addressed the determinants of the decision on crop insurance at the farm's micro level. In this article, both the financial and the agricultural literature lead to the identification of many rationales for the crop insurance decision. Using data from the period 2003–2006 on a representative survey of French farms (FADN‐RICA), we investigate the different factors that incite farmers to insure against crop risk. We emphasize that the highest risk farms are more likely to have insurance and this decision is positively related to the past amount of claims. Insurance is subscribed by larger farms because insurance appears too expensive for smaller farms, which are indeed naturally less diversified. Interestingly, financial variables (such as capital structure or return on investment) do not significantly determine the insurance decision.     

Impact of copula choice on the modeling of crop yield basis risk

A number of problems in agricultural economics involve modeling joint distributions for which the assumption of multivariate normality may not be warranted. Yet, very little work has been conducted evaluating competing methods for modeling joint dependence. We develop a simulation framework to evaluate the bias and efficiency impacts of copula choice in the context of evaluating county‐to‐farm basis risk. The results suggest significant differences in performance across various copulas and approaches. The findings have important implications for risk analysis, insurance, and policy modeling problems in agriculture regarding the selection of method to model dependence among random variables.     

Warming temperatures will likely induce higher premium rates and government outlays for the U.S. crop insurance program

Likely climate change impacts include damages to agricultural production resulting from increased exposure to extreme heat. Considerable uncertainty remains regarding impacts on crop insurance programs. We utilize a panel of U.S. corn yield data to predict the effect of warming temperatures on the mean and variance of yields, as well as crop insurance premium rates and producer subsidies. While we focus on corn, we demonstrate that the subsidy impacts are likely to carry over to other major program crops. We find that warming decreases mean yields and increases yield risk on average, which results in higher premium rates. Under a 1°C warming scenario, we find that premium rates at the 90% coverage level will increase by 39% on average; however, there is considerable statistical uncertainty around this average as the 95% confidence interval spans from 22% to 61%. We also find evidence of extensive cross‐sectional differences as the county‐level rate impacts range from a 10% reduction to a 63% increase. Results indicate that exposure to extreme heat and changes in the coefficient of variation are large drivers of the impacts. Under the 1°C warming scenario, we find that annual subsidy payments for the crop insurance program could increase by as much as $1.5 billion, representing a 22% increase relative to current levels. This estimate increases to 3.7 billion (57%) under a 2°C warming scenario. Our results correspond to a very specific counterfactual: the marginal effect of warming temperatures under current technology, production, and crop insurance enrollments. These impacts are shown to be smaller than the forecasted impacts under a commonly used end‐of‐century general circulation model for even the most optimistic CO₂ emissions projection.     

Collateral‐free lending with risk‐contingent credit for agricultural development: indemnifying loans against pulse crop price risk in India

This article addresses the problem of collateral‐free lending in the context of agricultural development. We investigate a viable alternative to traditional credit products through the development of risk‐contingent credit for operating loans and farm mortgages and apply the concept to agricultural loans for pulse crops in India. Risk‐contingent credit mitigates business and financial risk by reducing debt obligations depending on the embedded commodity options whose payoffs are linked with commodity price fluctuations. We analyze daily commodity spot prices for pulse crops in India and show how risk‐contingent structured financial instruments can be priced in practice.     

The efficiency of composite weather index insurance in hedging rice yield risk: evidence from China

As an economic and market‐transparent program, weather index insurance is expected to mitigate asymmetric problem. Capturing the relationship between yield and weather factor(s) is the basis of index insurance, but remains a challenge for weather index schemes. Meanwhile, composite weather index insurance is needed by farmers when their agricultural activities involve several risks, but is rarely studied. We aim to design a composite weather index insurance model and evaluate its efficiency in hedging yield risk by using the case of rice production in China. We divide the whole growth cycle of rice into six stages on the basis of agronomic knowledge, and use the average value of each weather factor in each stage to design a weather index. Then, the efficiency of composite weather index insurance is evaluated by mean‐semivariance and value‐at‐risk methods. First, we find that subdivision of the growth cycle helps to better capture the subtle relationship between rice yield and weather factors. Second, composite weather index insurance evidently reduces yield risk. Our findings help further adoption of weather index insurance in agricultural fields.     

Drought‐tolerant rice,weather index insurance,and comprehensive risk management for smallholders: evidence from a multi‐year field experiment in India

In rainfed production systems throughout India, agricultural activities are dependent upon the summer monsoon, and any aberration in monsoon rainfall patterns can have severe consequences for rice production. There is considerable policy interest in designing programs to lower small‐scale farmers’ exposure to these types of risk given the regularity with which adverse monsoon events occur. This paper introduces a field experiment conducted with two risk management options in the state of Odisha: a drought‐tolerant rice cultivar; and a weather index insurance product designed to complement the performance of the cultivar. Uptake rates for the cultivar itself and for the joint product are compared across two years alongside an analysis of factors that predict uptake. Results indicate high levels of demand for both the products, albeit with a significant degree of price sensitivity. But this sensitivity is agnostic to the nature of price reductions, suggesting that public investments that lower the costs of risk management may be sufficient to encourage broad uptake, without necessarily relying upon distortionary subsidies as is so often done. Sustained demand between years one and two is primarily explained where individuals were indemnified in year one and had a large number of peers also purchasing the product.     

Demand for a labor‐based drought insurance scheme in Ethiopia: a stated choice experiment approach

Index‐based weather insurance is increasingly used to manage weather‐related risks in smallholder agriculture. However, cash‐constrained smallholders often lack the resources to pay an insurance premium, which may undermine its wider adoption. This article investigates alternative insurance payment methods that may help to enhance the adoption of index‐based weather insurance. We use a choice experiment to elicit smallholders’ willingness to pay in cash or labor for index‐based weather insurance in four districts in the south‐central highlands of Ethiopia. The insurance schemes were created using a fractional factorial design with three factors: work, cash, and payout rate. We analyze the choice data using a random parameter mixed logit model. We find that the average participants need a subsidy to pay cash for insurance because their willingness to pay is less than the expected cost of the insurance. On average, they are willing to pay only 0.81 ETB (Ethiopian currency) to get an expected yearly payout of 1 ETB. However, most are willing to participate in work‐for‐insurance programs at lower daily wage rates than is common for other work programs in Ethiopia.     

Cash crop choice and income dynamics in rural areas: evidence for post‐crisis Indonesia

In this article we investigate the factors affecting levels and growth of incomes in rural Indonesia following the crisis of 1997–1998. In particular, we investigate the relative roles of nonfarm incomes and productivity improvements achieved via changes in crops versus improvements on the same crops on income dynamics. Framing the article in the context of an optimal labor allocation model, relying on unique household panel data from Central Sulawesi, and using advanced panel econometric methods, we find that local innovations related to the adoption and intensification of new cash crop varieties, more specifically the shift from coffee to cocoa production, can explain a substantial part of the observed post‐crisis developments. Causal estimates of the effect of growing cocoa suggest that households were on average able to achieve about 14% higher income levels during the post‐crisis period compared to the planting of other crops, most notably coffee. Also, our results demonstrate the importance of engagement in nonfarm activities for household income growth. Comparative analyses using a nationally representative survey suggest that similar processes are at play in other parts of Indonesia.     

Agent‐based modeling for ex ante assessment of tree crop innovations: litchis in northern Thailand

This study uses an agent‐based model for ex ante assessment of agricultural innovations. The model builds on whole farm mathematical programming (MP) and extends the methodology with a spatial representation of the system, the heterogeneity of farm households and landscapes, and the interaction between farm households. We apply the model in a northern Thai watershed to study the potential of four innovations to increase the profitability of litchi orchards. Cost‐benefit analysis shows that each innovation would increase the profitability of litchi growing; however, the results of the agent‐based model show that at current price levels these innovations alone would not be enough to stem the decline in the area under litchis. The model was validated and the sensitivity of the results tested for variations in the irrigated water supply and liquidity. We report on how farmers responded to these results and discuss the implications for other areas in northern Thailand.     

Adoption of farm‐based irrigation water‐saving techniques in the Guanzhong Plain,China

This article analyses adoption of farm‐based irrigation water saving techniques, based on a cross‐sectional data set of 357 farmers in the Guanzhong Plain, China. Approximately 83% of the farmers use at least one farm‐based water‐saving technique. However, the traditional, inefficient techniques border and furrow irrigation are still prevalent whereas the use of advanced, more efficient techniques is still rather rare. We develop and estimate an adoption model consisting of two stages: awareness of water scarcity and intensity of adoption. We find that awareness of water scarcity and financial status enhance adoption of more advanced techniques whereas access to better community‐based irrigation infrastructure discourages it. We furthermore find both community‐based irrigation infrastructure and farm‐based irrigation water‐saving techniques have mitigating effects on production risk. From the results it follows that adoption can be stimulated via financial support and via extension aimed at enhancing awareness of water scarcity.     

Feasibility of risk‐based inspections in organic farming: results from a probabilistic model

A risk‐based inspection system might improve the efficiency of the organic farming certification system and ultimately provide a basis for increased competitiveness of this sector. This requires the definition of an effective inspection procedure that allows statistical evaluation of critical risk factors for noncompliance. In this article, we present a study based on data from selected control bodies in five European countries that is aimed at determining the feasibility of risk‐based inspections in the organic sector according to the data that are currently routinely recorded. Bayesian networks are used for identification of the factors that can affect the risk of noncompliance. The results show that previous/concurrent noncompliant behavior explains most of the risk, and that the risk increases with farm size and the complexity of their operations. The data currently recorded by control bodies appear to be insufficient to establish an effective risk‐based approach to these inspections.     

Evaluating the Potential of Index Insurance Schemes to Reduce Crop Yield Risk in an Arid Region

We evaluate yield risk reduction through weather index, area yield index and farm yield insurance contracts for wheat farms in Kazakhstan by employing data from 1980 to 2002. We use the usual mean variance (MV) approach and also a second‐degree stochastic dominance (SSD) criterion. While MV is not necessarily consistent with the expected utility (EU) theory, SSD results only in a minimum but EU‐consistent benefit from insuring. Differences in the estimation results for both approaches underline the advantage of applying both criteria to analyse the risk‐reducing potential of crop insurance. Bootstrapping results show that none of the analysed insurance schemes provides statistically significant risk reduction for every single farm. In addition, weather‐based index insurance is found to provide less risk reduction than area yield insurance based on the rayon (county) yield. Moreover, rayon yield index insurance can reduce yield risk more effectively for Kazakhstan's wheat producers than farm yield insurance with a low strike yield.     

Adoption of weather‐index insurance: learning from willingness to pay among a panel of households in rural Ethiopia

In this article we examine which farmers would be early entrants into weather‐index insurance markets in Ethiopia, were such markets to develop on a large scale. We do this by examining the determinants of willingness to pay for weather insurance among 1,400 Ethiopian households that have been tracked for 15 years as part of the Ethiopian Rural household Survey. This provides both historical and current information with which to assess the determinants of demand. We find that educated, wealthier individuals are more likely to purchase insurance. Risk aversion is associated with low insurance take‐up suggesting that models of technology adoption can inform the purchase and spread of weather index insurance. We also assess how willingness to pay varied as two key characteristics of the contract were varied and found that basis risk reduces demand for insurance particularly when the price of the contract is high, and that provision of insurance through groups is preferred by female headed households and individuals with lower levels of education.     

Off‐farm work,technical efficiency,and rice production risk in Taiwan

This article investigates the differences in yield production, production efficiency, and yield risk for farmers both with and without off‐farm work. Using a nationwide survey of rice farmers in Taiwan, we estimate two stochastic production frontier models that accommodate technical inefficiency and production risk simultaneously for farmers both with and without off‐farm work. The stochastic dominance criterion is then applied to compare the differences in the distributions of the estimated technical efficiency and yield risk between groups. The empirical results indicate that these two groups of farmers use resources in different ways, and off‐farm work is not necessarily associated with lower technical efficiency. For farmers in the lower percentiles of the efficiency distribution, those with off‐farm work are more efficient than their counterparts without off‐farm work. In addition, farmers with off‐farm work face higher production risk and this result is robust for the entire distribution.