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Introduction: Weather-based index insurance is a financial instrument which allows smallholder farmers to protect themselves against climate shocks such as droughts and floods. In many cases, insurance indices are based on one or more earth observation datasets (e.g., rainfall, soil moisture, vegetative health) which are partly covering periods of more than 40 years. While remote sensing products and their associated data have improved over this time, understanding the historical climate variability and trends remains an essential piece in ensuring the development of indexes that best represent farmers' risks. From a practical perspective, shortening time series to limit the risk of understudied climate variability, such as the Atlantic Multidecadal Variability, sometimes seems to be a quick solution. However, shorter time series jeopardize the overall robustness of the index. Therefore, understanding the links between climate variability, index design, and implications for farmers is key. Weather-based index insurance products in Sahelian West Africa usually face a challenge in robustly quantify underlying climatic decadal variation in seasonal rainfall. Methods: This study analyzes the influence of decadal shifts in rainfall patterns in Sahelian West Africa, in particular Senegal, on index insurance calibration and design, concluding with practical recommendations for the next generation of drought risk finance instruments in the region. Results: Our findings indicate that decadal variability has not led to a clear decrease in payouts in recent years compared to earlier years, despite an overall increase in seasonal rainfall. Rather, we find that interannual variability has increased which may be a more critical factor for assessing farmers' agricultural risk than the increase in total rainfall. Discussion: Focusing on key moments of the cropping calendar in the design of an index shows that an increase in the total average rainfall per season does not result in fewer payouts. [ABSTRACT FROM AUTHOR]

Weather risk affects the economy, agricultural production in particular. Index insurance is a promising tool to hedge against weather risk, but current piecewise-linear index insurance contracts face large basis risk and low demand. We propose embedding a neural network-based optimization scheme into an expected utility maximization problem to design the index insurance contract. Neural networks capture a highly nonlinear relationship between the high-dimensional weather variables and production losses. We endogenously solve for the optimal insurance premium and demand. This approach reduces basis risk, lowers insurance premiums, and improves farmers' utility. This paper was accepted by Agostino Capponi, finance. Funding: This work was supported by the Research Grants Council, University Grants Committee [Grants GRF 16502020, GRF 16504522, and T31-603/21-N], Singapore Ministry of Education Academic Research Fund Tier 1 [Grants RG143/19 and RG55/20], the Natural Sciences and Engineering Research Council of Canada [Grants RGPIN-2021-04144 and DGECR-2021-00330], the Research Database Matching Fund, and the School of Business and Management, Hong Kong University of Science and Technology. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4902. [ABSTRACT FROM AUTHOR]

IntroductionWeather-based index insurance is a financial instrument which allows smallholder farmers to protect themselves against climate shocks such as droughts and floods. In many cases, insurance indices are based on one or more earth observation datasets (e.g., rainfall, soil moisture, vegetative health) which are partly covering periods of more than 40 years. While remote sensing products and their associated data have improved over this time, understanding the historical climate variability and trends remains an essential piece in ensuring the development of indexes that best represent farmers’ risks. From a practical perspective, shortening time series to limit the risk of understudied climate variability, such as the Atlantic Multidecadal Variability, sometimes seems to be a quick solution. However, shorter time series jeopardize the overall robustness of the index. Therefore, understanding the links between climate variability, index design, and implications for farmers is key. Weather-based index insurance products in Sahelian West Africa usually face a challenge in robustly quantify underlying climatic decadal variation in seasonal rainfall.MethodsThis study analyzes the influence of decadal shifts in rainfall patterns in Sahelian West Africa, in particular Senegal, on index insurance calibration and design, concluding with practical recommendations for the next generation of drought risk finance instruments in the region.ResultsOur findings indicate that decadal variability has not led to a clear decrease in payouts in recent years compared to earlier years, despite an overall increase in seasonal rainfall. Rather, we find that interannual variability has increased which may be a more critical factor for assessing farmers’ agricultural risk than the increase in total rainfall.DiscussionFocusing on key moments of the cropping calendar in the design of an index shows that an increase in the total average rainfall per season does not result in fewer payouts.

Abstract Drought-induced risk endangers farmers in arid and semi-arid regions. Insurance is recognized as an appropriate policy alternative to support farmers facing with financial losses associated with production reduction. In this context, present study developed an ex ante index-based insurance program to deal with drought-induced risk of production losses. We applied this model to wheat growers in Iran. After the calibration of the contract parameters, an insurance scheme was optimized and tested. We showed that optimal insurance contracts generate low gain of certain equivalent income, high compensation, and a high basis risk. The best contract was not proportional to the complexity of the proposed index. The insurance program studied is recommended as a proper alternative for currently applying yield insurance.

Crop farmers in arid and semi-arid regions face a covariate risk that is of paramount importance, namely, the threat of catastrophic crop loss triggered by natural disasters and climate hazards. Such an occurrence not only jeopardizes the livelihoods of these farmers but may also lead to persistent poverty. Promoting sustainable development requires control over climate-related shocks, which negatively affect the most vulnerable population in the developing world. This study investigates the option of choosing crop area-yield index insurance to mitigate the adverse effects associated with climate stress. In addition, we assessed the amount farmers are willing to pay for an insurance product that insures yields below 70% of the local average in the study area. Our results show that access to extension services and economic association membership offers farmers social capital and encourages their decision to purchase index insurance. We also find that the long-run welfare impact of index insurance policy on vulnerable households could be significant as an alternative insurance mechanism to traditional insurance. This study contributes to filling the gaps on the uptake of index insurance and provide guidance to policymakers in their approach to mitigating the effects of climate change on crop production in Nigeria. [ABSTRACT FROM AUTHOR]

Strengthening climate resilience requires farmers to select climate adaptation strategies like weather index insurance. Acknowledging that decision-making is not isolated, this study explores simultaneous peer imitation in climate adaptation choices consisting of index insurance, savings, and their interaction. We present results from a lab-in-the-field experiment that introduces innovative index insurance. Findings indicate significant and strong imitation attitudes. While the bigger peer surrounding seems relevant in the static perspective, the closer surrounding gains importance in the dynamic perspective. Additionally, credit, trust, and practical understanding stimulate adoption. Community-based extension interventions and credit-bundled products may increase index insurance diffusion and improve climate resilience. [ABSTRACT FROM AUTHOR]

Index insurance is a promising tool to reduce the risk faced by farmers, but high basis risk, which arises from imperfect correlation between the index and individual farm yields, has limited its adoption to date. Improving adoption will require reducing one or both of the two fundamental sources of basis risk: the intrinsic heterogeneity within an insurance zone (zonal risk), and the lack of predictive accuracy of the index (design risk). Previous work has focused mostly on design risk, conflating the quality of the index with the quality of the zone. Consequently, there is currently no way to distinguish a "good index in a bad zone" from a "bad index in a good zone". Here we investigate the relative roles of zonal and design risk, with two main contributions. First, using a formal decomposition of basis risk, we show that the optimal index is the first principal component of the correlation matrix of yields between fields. This provides a simple upper bound on the insurable basis risk that any index can reach within a given zone. Second, we use 10 m resolution satellite data on maize yields in Kenya to provide the first large‐scale empirical analysis of the extent of zonal versus design risk. Our results show a strong local heterogeneity in yields, underscoring the challenge of implementing index insurance in smallholder systems and the potential benefits of low‐cost yield measurement approaches that can enable more local definitions of insurance zones. [ABSTRACT FROM AUTHOR]

Agricultural risks, given climate change and the crisis of globalization, are increasingly considered as national security risks. In global practice, insurance has proven to be one of the most successful and sustainable ways to manage agricultural risks. In the Russian Federation, agricultural insurance is also state-supported, which emphasizes the importance of containment of agricultural sector hazards. However, the level of insurance penetration in Russian agriculture is insufficient. Indices in agricultural insurance, i.e. insurance in which insurance payments are made not on the basis of the assessment of damage to the insurance object, but on the basis of the behavior of a special index, are used in many countries around the world. The main idea of index insurance is that there is no need to establish the fact and calculate the amount of loss, which makes it especially demanded for those activities in the real sector of the economy where speed, transparency and simplicity of insurance payments are important, as well as the need to attract additional well-trained employees to carry out the insurance process and claims settlement. Reduced workload due to the absence of the need to calculate the amount of loss reduces the time required to process claims. The procedures of claim settlement in index insurance can be called the most simplified for the client and the least costly for the insurance company, but the advantages and positive features of index insurance do not end there. The authors have investigated and systematized the possibilities of index insurance, for which they also considered the successful experience of a country with similar socio-cultural codes, Mexico, in the field of agricultural index insurance. The article also suggests ways to overcome the difficulties of index insurance implementation in the Russian insurance realities. The positive features of the index insurance identified by the authors can make it a promising alternative to classical (traditional) insurance, including for the further development of agricultural insurance with state support.

We utilize over 190,000 historical farm‐level dryland row‐crop yield observations (corn, sorghum, soybeans, and winter wheat) spanning over 7000 Kansas farms from 1973 to 2018 coupled with agroclimatic variables to assess the performance of a broad range of weather‐ and area‐based insurance products. Results showed substantial levels of basis risk across agroclimatic‐based indices, limited ability to reduce income variability under fair pricing, and underperformance relative to area‐based yield products. Growth‐stage specific heat indices for corn and soybeans may offer an effective risk management tool. Implications in the context of current agricultural policy initiatives and climate change adaptation are discussed. [ABSTRACT FROM AUTHOR]

The adoption of advanced agricultural technologies in Sub‐Saharan Africa remains disappointingly low, particularly among the millions of poor smallholders who account for most of the agricultural production. We conducted a randomized control trial in Ghana to assess the impact of easing drought‐risk constraints in the agricultural credit market, by bundling joint liability agricultural loans with index insurance, on smallholder farmers' agricultural technology adoption decisions. In the micro‐insurance treatment, any index insurance payouts go directly to farmers, while in the meso‐insurance treatment, payouts are issued to banks to be used to expunge farmers' debts. We find evidence that bundling joint liability lending with micro‐insurance increases adoption of fertilizer. [ABSTRACT FROM AUTHOR]

Remotely sensed data have the potential to monitor natural hazards and their consequences on socioeconomic systems. However, in much of the world, inadequate validation data of disaster damage make reliable use of satellite data difficult. We attempt to strengthen the use of satellite data for one application—flood index insurance—which has the potential to manage the largely uninsured losses from floods. Flood index insurance is a particularly challenging application of remote sensing due to floods’ speed, unpredictability, and the significant data validation required. We propose a set of criteria for assessing remote sensing flood index insurance algorithm performance and provide a framework for remote sensing application validation in data-poor environments. Within these criteria, we assess several validation metrics—spatial accuracy compared to high-resolution PlanetScope imagery (F1), temporal consistency as compared to river water levels (Spearman's ρ), and correlation to government damage data (R2)—that measure index performance. With these criteria, we develop a Sentinel-1 flood inundation time series in Bangladesh at high spatial (10 m) and temporal (∼weekly) resolution and compare it to a previous Sentinel-1 algorithm and a Moderate Resolution Imaging Spectroradiometer (MODIS) time series used in flood index insurance. Results show that the adapted Sentinel-1 algorithm (F1avg = 0.925, ρavg = 0.752, R2 = 0.43) significantly outperforms previous Sentinel-1 and MODIS algorithms on the validation criteria. Beyond Bangladesh, our proposed validation criteria can be used to develop and validate better remote sensing products for index insurance and other flood applications in places with inadequate ground truth damage data.

Purpose: Index insurance is promising to mitigate drought-related income losses in agriculture. To reduce the basis risk of index insurance, the integration of satellite data is of growing interest in research. The objective of this study is to obtain preliminary evidence regarding farmers' perceived usefulness (PU) of satellite-based index insurance. Design/methodology/approach: By modifying the transtheoretical model of change to a transtheoretical model of PU, German farmers' gradual PU of satellite-based index insurance was investigated. Findings: The results show that the average farmer perceives satellite-based index insurance as useful. It can be particularly seen that a higher level of education in an agricultural context as well as higher trust in index insurance products increases farmers' gradual PU. Moreover, higher relative weather-related income losses increase farmers' gradual PU. Research limitations/implications: It is recommended to apply latent variables when conducting future investigations regarding farmers' PU. Originality/value: To the best of the authors' knowledge, this is the first study to explore farmers' PU of upcoming satellite-based index insurance by modifying and applying the transtheoretical model in a new way. [ABSTRACT FROM AUTHOR]

There are several index insurance methodologies. Most of them rely on linear piece-wise methods. Recently, there has been studies promoting the potential of data-driven methodologies in construction index insurance models due to their ability to capture intricate non-linear structures. However, these types of frameworks have mainly been implemented in high-income countries due to the large amounts of data and high-frequency requirements. This paper adapts a data-driven methodology based on high-frequency satellite-based climate indices to explain flood risk and agricultural losses in the Antioquia area (Colombia). We used flood records as a proxy of crop losses, while satellite data comprises run-off, soil moisture, and precipitation variables. We analyse the period between 3 June 2000 and 31 December 2021. We used a logistic regression model as a reference point to assess the performance of a deep neural network. The results show that a neural network performs better than traditional logistic regression models for the available loss event data on the selected performance metrics. Additionally, we obtained a utility measure to derive the costs associated for both parts involved including the policyholder and the insurance provider. When using neural networks, costs associated with the policyholder are lower for the majority of the range of cut-off values. This approach contributes to the future construction of weather insurance indexes for the region where a decrease in the base risk would be expected, thus, resulting in a reduction in insurance costs. [ABSTRACT FROM AUTHOR]

Pastoralists in sub-Saharan Africa are particularly vulnerable to changing climatic conditions and heavily affected by an increasing frequency of severe droughts. To increase drought resilience, livestock index insurance constitutes a promising tool that is aligned to mitigate covariate risks. Uptake rates for these products are, however, relatively low. This article uses choice-experimental data collected in Northern Kenya to analyse preferences for hypothetical livestock index insurance contracts among pastoralists. Results show that pastoralists prefer lower strike levels as well as transparency in the form of regular radio announcements and text messages informing the policyholder about the location-specific index readings. Highly valued are trust enhancing features such as an index certification. We do not find any indication that the option to split the premium payment into two instalments as a way to relax potential liquidity constraints could lead to higher demand. [ABSTRACT FROM AUTHOR]

Index insurance has been promoted as an innovative strategy for enhancing long-term resilience to climate-related shocks and providing financial inclusion, particularly to poor women farmers in developing countries. In this paper, we evaluate the gendered impact of an index-based livestock insurance product on food consumption among pastoral households in southern Ethiopia. We exploit intertemporal variation in household risk exposure and insurance payouts to evaluate the ex ante and ex post insurance impacts and use randomly distributed discount coupons to instrument the insurance purchase variables. We find that during the pre-drought period, a previous season insurance purchase and the intensity of insurance coverage significantly and equally reduces food expenditure in male- and female-headed households. In the post-drought period, we find that an insurance payout significantly increases food expenditure per adult equivalent among female-headed households.

This article presents a novel methodology to assess the financial risk to crops in highly weather-volatile regions. We use data-driven methodologies that use singular value decomposition techniques in a low-income economy. The risk measure is first derived by applying data-driven frameworks, a Principal Component Analysis (PCA), and Singular Spectrum Analysis (SSA) to productive coffee crops in Colombia (163 weather stations) during 2010–2019. The objective is to understand the future implications that index insurance tools will have on strategic economic crops in the country. The first stage includes the identification of the PCA components at the country level. The risk measure, payouts-in-exceedance ratio, or POER, is derived from an analysis of the most volatile-weather-producing regions. It is obtained from a linear index insurance model applied to the extracted singular-decomposed tendencies through SSA on first-component data. The financial risk measure due to weather volatilities serves to predict the future implications of the payouts-in-exceedance in both seasons—wet and dry. The results show that the first PCA component contributes to forty percent of the total variance. The seasonal forecast analysis for the next 24 months shows increasing additional payouts (PO), especially during the wet season. This is caused by the increasing average precipitation tendency component with POERs of 18 and 60 percent in the first and second years. The findings provide important insights into designing agricultural hedging insurance instruments in low-income economies that are reliant on the export of strategic crops, as is the case of Colombian coffee. [ABSTRACT FROM AUTHOR]

Basis risk or residual risk arising from disparity between an index's estimate of losses and actual losses is inherent in index-based insurance products. We approximate basis risk as the false negative probability (FNP) within pasture, rangeland, and forage (PRF) rainfall index insurance for the south-central coastal region of California. We estimate the FNP on average that at least one of two selected coverage intervals will fail to provide an indemnity when a loss is realized at 48%. The average FNP is reduced to only 11% when considering whether both selected intervals fail to provide an indemnity when a loss is realized. [ABSTRACT FROM AUTHOR]

This study investigates the willingness to pay (WTP) for index-based drought insurance coupled with agricultural loans by product design and gender, using a contingent valuation method. The empirical estimations reveal several important findings. First, females have lower mean WTP than male farmers for each product design. Second, females do not express preference differences between insured loan product designs while males do. In fact, males prefer insured loans that make payouts directly to them and prefer insured loans without design risk. [ABSTRACT FROM AUTHOR]

Research shows that risk management will be key if an agricultural transformation that includes the smallholder farm sector is to occur in sub‐Saharan Africa and South Asia. While the smallholder farm sector has historically had poor access to financial and other risk management tools, digital technologies are rapidly impacting the cost and availability of savings, credit, and insurance services in remote rural regions. While these services are all different ways of moving money through time, and thus would seem to be substitutes for each other, they are characterized by quite different pre‐requisites in terms of trust and understanding, and in terms of required tangible and reputational assets. This observation suggests that resilience and an inclusive agricultural transformation might be best promoted by a flexible system that offers indexed risk management tools that can meet the needs of households that enjoy different assets and beliefs. This article lays out this logic and models the use and impacts of a system of flexible financial tools for risk management and an inclusive agricultural transformation. Key findings include that farmers will optimally combine all three financial instruments. The model also shows that these combined financial risk management tools are by themselves sufficient to induce agricultural intensification for less poor, but not for the deeply poor households who have already been decapitalized by shocks. [ABSTRACT FROM AUTHOR]

Index insurance offers an innovative risk management solution for uninsured agricultural weather risk. We investigate the theoretical relationship between prospect theory risk preferences and characteristics of index insurance. We pair these theoretical findings with data from a lab-in-the-field experiment in Kenya. Empirically, we find that insurance demand is decreasing in loss aversion, and the negative marginal effect of loss aversion on insurance demand increases with basis risk and the insurance premium. Our theoretical and empirical results combined illustrate the importance of considering both risk and loss aversion, as well as basis risk, in understanding index insurance decisions. [ABSTRACT FROM AUTHOR]

Water scarcity is an increasingly recurring problem for irrigated agriculture in Mediterranean regions. It is, therefore, necessary to establish technical and financial measures to enable irrigators to deal with this problem. This study presents a new index-based drought insurance scheme in an irrigation district in the Jucar river basin in Spain, a highly regulated water system. Three insurance scheme options were evaluated and, the values of the fair risk premiums, the maximum compensation, and the deductible franchise were established. These insurance schemes were designed in agreement with the preexisting drought system operating rules to reduce moral hazard and adverse selection. Risk-reducing and effective evaluation methods were used to determine the insurance coverage's viability for irrigators: standard deviation gross margin, minimum gross margin, and RMSL. The proposed insurances were also evaluated using synthetic hydrological time series generated with a stochastic ARMA model through a basin-wide water resource simulation model developed in the DSS Shell AQUATOOL. Financial indicators, such as the basis risk and claim ratio were applied to analyze the economic feasibility for insurance companies. The results show that a suitable and efficient option is an early-bird contract combined with a trigger of emergency or alert state in a multi-year contract. This type of specialized insurance helps to fill the existing gap in traditional insurance schemes for irrigated crops and offered additional coverage to farmers under drought and water scarcity conditions. [ABSTRACT FROM AUTHOR]

Geographers have interpreted the rise of weather insurance for small agricultural producers as emblematic of financialization's inexorable march to capitalize the countryside. Yet this market has proved far less successful than advocates hoped or critics feared. Rather than a speculative tool for surplus extraction from smallholders or a mechanism for their financial subjectification, this article reinterprets weather insurance as an infrastructure of concessionary transfers from the development sector to make market-mediated mechanisms work. These transfers are emblematic of the new distributional terms struck between donors, states, and insurance capital as financial risk transfer is articulated with the extension of fragmentary safety nets. Economic field experiments with insurance have proliferated as venues in which the value of insurance is tested by both economists and experimenting subjects. Just as data from these trials have suggested some positive welfare impacts, they have also indicated target clients are unwilling or unable to pay full market price, thus performing a new justification for the perpetual presence of subsidies. Such transfers present opportunities for reinsurers to command rents through their control of large pools of capital and their interpretive authority over techniques for pricing risk under uncertainty. In a changing climate, reinsurers are poised to collect larger rents from donors' and governments' premium subsidies meant to decrease insurance costs for the vulnerable. These dynamics of rent cycling underscore the urgency of building more equitable, systematic risk-sharing infrastructures to replace the current fragmentary archipelagos of weather insurance. [ABSTRACT FROM AUTHOR]

Agricultural producers who are reliant upon rangelands and pasturelands are some of the most vulnerable to weather‐related risk given their dependence on climate‐sensitive resources. Index‐based insurance products, like the Pasture, Rangeland, and Forage Insurance Program, are considered to be an adaptation strategy for mitigating climatic risks. Given that indices are imperfect predictors of losses, residual (basis) risk persists. This study quantifies basis risk and assesses insurance contract quality for nearly 63 million acres of rangelands in California. Basis risk can be summarized by considering false negative probabilities—the probability that an insured producer suffers a loss without receiving an indemnity payment. On California rangelands the false negative probabilities associated with one (both) of insured time intervals failing to indemnify a loss are 31% to 46% (14%–25%). When indemnities were paid, in 36% of the cases the payments are not sufficient to compensate for forage‐related losses; the average shortfall in indemnity‐related compensation ranged from $1.74/acre to $2.73/acre depending upon the location and underlying value of forage. [ABSTRACT FROM AUTHOR]

Despite donor assistance and government subsidies, the uptake of microinsurance products to insure against extreme climate events remains low in many climate vulnerable economies. Emerging evidence indicates that various non-price factors such as lack of knowledge, trust in institutions, beliefs, and perceptions about climate change partly explain the low uptake. This study uses the CVM approach to investigate the effect of one such factor – farmers' climate change perceptions – on the adoption of weather index micro-insurance. We introduce two hypothetical weather index microinsurance products to farming households in Nepal: the first one (basic) insures paddy only, whereas the second one (comprehensive) also insures livestock. We use bivariate probit models with order effects for empirical estimation. We find that households' ex ante perception of future climate change as well as their ex-post perceptions of past climate change impacts have significant effects on their microinsurance purchase decisions. Mean WTP-values for the basic and comprehensive products are NRs. 3096 and NRs. 13209 respectively. We also find some evidence of crowding-out effects on private risk transfer markets by other public and donor climate adaptation programmes. Our findings suggest that public policies should focus on increasing climate awareness, accountability and the development of competitive microinsurance markets. [ABSTRACT FROM AUTHOR]

There are several index insurance methodologies. Most of them rely on linear piece-wise methods. Recently, there has been studies promoting the potential of data-driven methodologies in construction index insurance models due to their ability to capture intricate non-linear structures. However, these types of frameworks have mainly been implemented in high-income countries due to the large amounts of data and high-frequency requirements. This paper adapts a data-driven methodology based on high-frequency satellite-based climate indices to explain flood risk and agricultural losses in the Antioquia area (Colombia). We used flood records as a proxy of crop losses, while satellite data comprises run-off, soil moisture, and precipitation variables. We analyse the period between 3 June 2000 and 31 December 2021. We used a logistic regression model as a reference point to assess the performance of a deep neural network. The results show that a neural network performs better than traditional logistic regression models for the available loss event data on the selected performance metrics. Additionally, we obtained a utility measure to derive the costs associated for both parts involved including the policyholder and the insurance provider. When using neural networks, costs associated with the policyholder are lower for the majority of the range of cut-off values. This approach contributes to the future construction of weather insurance indexes for the region where a decrease in the base risk would be expected, thus, resulting in a reduction in insurance costs.

Objective: this article studies the efficiency of a novel regression approach, the geographically weighted quantile lasso (GWQlasso), in the modeling of yield-index relationship for weather index insurance products. GWQlasso allows regression coefficients to vary spatially, while using the information from neighboring locations to derive robust estimates. The lasso component of the model facilitates the selection of relevant explanatory variables. Methodology: a weather index insurance (WII) product is developed based on one-month standardized precipitation index (SPI) derived from a daily precipitation dataset for 41 weather stations in the state of Paraná (Brazil) for the period from 1979 to 2015. Soybean yield data are also used for the 41 municipalities from 1980 to 2015. The effectiveness of the GWQlasso product is evaluated against a classic quantile regression approach and a traditional yield insurance product using the spectral risk measure (SRM) and the mean semi-deviation. Results: while GWQlasso proved as effective as quantile regression, it outperformed the yield insurance product. Conclusion: the GWQlasso is an alternative to the crop insurance market in Brazil and other locations with limited data. [ABSTRACT FROM AUTHOR]

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Households in developing countries commonly engage in risk sharing to cope with shocks. Despite this, the residual risk they remain exposed to — often due to aggregate events such as droughts and floods — is considerable. To mitigate these risks, governments, NGOs and multilateral organizations have introduced index insurance. To appreciate its welfare implications, however, it is necessary to assess how insurance interacts with pre-existing risk sharing. We ask to what extent the demand for index insurance — as compared to standard indemnity insurance — depends on the level of pre-existing risk sharing. We contribute by developing a simple theoretical framework which shows that, relative to a state of autarky, risk sharing between agents increases demand for index insurance and decreases demand for indemnity insurance. In an artefactual field experiment with Ethiopian farmers who share risk in real life, we test and confirm these predictions. [ABSTRACT FROM AUTHOR]

We investigate the impact of optimizing a portfolio of Drought-Tolerant Maize Varieties (DTMVs) to manage weather risk and its implications on the development of sustainable micro-insurance markets. We use high-resolution climate data and on-farm trial data, involving 20 DTMVs, over 49 locations spanning eight countries in Africa and 5 mega-environments. Markov chain and multivariate spatial Bayes models are employed to generate multivariate space-time rainfall and maize yield distributions, and derive optimal semi-variance portfolio of DTMVs. We find that optimal portfolios significantly outperformed naive portfolios, overall, reducing insurance premium rates by 31–55%. [ABSTRACT FROM AUTHOR]

There is widespread concern in developing countries with the expansion of formal insurance products to help manage significant risks. These concerns arise primarily from a lack of understanding of insurance products, general failures of financial literacy and the need to use relatively exotic products in order to keep costs down for poor households. We investigate the importance of incentivized measures for general understanding, as well as domain-specific knowledge of the decision context on the purchase and the quality of index insurance decisions. We evaluate the quality of financial decisions by comparing the individual expected welfare outcomes of a number of decisions each individual makes to purchase index insurance or not. We find that excess purchase is an important driver of welfare losses, and that our incentivized measure of domain-specific literacy plays a critical role in bringing about better quality index insurance decisions. [ABSTRACT FROM AUTHOR]

This paper examines whether agricultural insurance can boost investment by small scale farmers in West Africa. It is based on a randomized evaluation designed to analyze the impacts of index insurance for cotton farmers in Burkina Faso. No impact of insurance was found on cotton, but, consistent with microeconomic theory, significant spillover impacts on investment in other agricultural activities were measured. Furthermore, the effects of insurance payouts on farmers hit by a shock confirm the potential of index insurance as a risk-management tool. However, this research uncovers important flaws in the implementation of the project that limited its impact on cotton. Overall, this study suggests a promising role for index insurance in stimulating investment, but also draws attention to key challenges to the efficient delivery of insurance to small farmers. Finally, the study's hybrid, mixed methods RCT offers lessons for the evaluation of complex interventions where trust, understanding, and timing are all important. [ABSTRACT FROM AUTHOR]

Purpose. The purpose of the paper is investigation of the development of the Ukrainian market of insurance products in agriculture with the identification and classification of factors that affect the dynamics of the main market indicators, and determination on this basis the conceptual directions of building an effective system of agricultural insurance in Ukraine. Methodology / method / approach. The methodology of the study consisted of the provisions of neoclassical and institutional theories; we used methods of generalization and systematization (by determining current trends in the development of the agricultural insurance market), periodization (to identify common features and differences in the formation of agricultural insurance in Ukraine), statistical analysis (to analyze the dynamics of agricultural development indicators, the agricultural insurance market), factor analysis (to determine the factors influencing the effectiveness of agricultural insurance); correlation and regression analyzes (by revealing dependence of development indicators of agricultural insurance market from macroeconomic indicators and volumes of state financing), prognostic (to formulate conclusions and proposals on conceptual vectors of development of agricultural insurance). Results. The study revealed a low level of penetration (implementation) of insurance in the agriculture of Ukraine. Agri-insurance is carried out mainly in crop production. Modern insurance products are presented in the Ukrainian insurance market, but their range is smaller than in the countries with developed agricultural insurance. Regulatory provision of insurance for agricultural products is represented by a large number of documents, the failure of which in full compliance with certain provisions, such as state subsidies for insurance premiums, impedes the development of agricultural insurance. We summarized and classified the factors of development of agricultural insurance in Ukraine and used a mathematical model to identify the main functional factors that influence the dynamics of insured areas. We established an important dependence of the development of agricultural insurance on a set of institutional and functional factors. Originality / scientific novelty. The systematic approach to the research of agricultural insurance as a constituent of conditions for sustainable development of the agrarian sphere was further developed. It is determined that implementation of potential opportunities of agricultural insurance as a component of ensuring conditions for sustainable development of the agrarian sector is hampered by the high cost of insurance premiums, insufficient amounts of financing of state programs, inconsistency of state policy, absence in its development and implementation of medium-term planning; incompleteness of information on the part of stakeholders regarding the necessity, availability of agricultural insurance. For the development of agricultural insurance, it is necessary to reduce the negative impact of such factors. Practical value / significance. The institutionalization of agricultural insurance, as one of the preconditions for the functioning of Ukrainian agriculture on the principles of sustainable development, will facilitate the transition from multi-risk to index insurance, the formation of a transparent regulatory environment, the introduction of medium-term state programming, the dissemination of information on the necessity, availability, expediency of agricultural insurance at the state level for the stakeholder.

The Republic of Serbia has very favourable opportunities for the development of crop production. Even so, Serbian farmers face many risks. Due to climate change, it is certain that there will be increasing fluctuations in temperature and rainfall, which will increase the production risks. In recent years, due to globalization and market liberalization, price risks have inevitably increased. On this basis, it is clear that the farmed s basic risks are related to the yield level and the price level of agricultural products. One of the external risk management instruments is insurance and there are two main groups of insurance: traditional and index insurance. The application of area-revenue insurance in agriculture, as a type of index insurance is becoming more and more popular in the last few years, especially in developed countries. This model is based on data related to average revenue of particular administrative unit or region and it represents the basis for premium calculation and insurance benefits. In the case of wheat production as one of the most important crops in the region of Kula municipality, the authors describe the methodology of application of the analysed insurance system. The main advantage of this insurance model is that it does not require the damage assessment and their implementation would reduce the negative financial consequences in Serbian agricultural production. In this way, this insurance model can be seen as a significant alternative to conventional insurance, which can increase insured area and number of insured, and trust and confidence in insurance companies would also be restored.

Weather-related hazards generate unfortunate risks, especially for low-income economies, such as populations dependent on agriculture. Index insurance offers structural advantages compared with conventional insurance, including moral hazard, adverse selection, and systemic risk. It also represents a promising financial tool because of its potential to provide timely economic relief after an unusual weather event by indemnifying policyholders based on the observed value of a particular index directly related to weather parameters. Because of these advantages, this type of insurance can potentially be extended to more crop-productive regions. This study examines the possible spread of weather index insurance programs for Arabica Coffee in Colombia in the short and medium terms in aggregated regions, according to the wet and dry crop seasons. Using a short historical precipitation data from 2010 to 2019 for 163 productive zones in 11 departments located at altitudes of 990–1,890 m, we use an unsupervised technique to first cluster the observations through mixture modeling. Then, we extract through singular spectrum analysis, the signal components of precipitation of each cluster and seasons to propose a simple index insurance model which determines the immediate payoff disbursals. We particularly identify the behavior of the tendency and seasonal payoffs. Finally, we forecast the tendency components in each cluster and season to derive a ratio of future payoffs in exceedance. This ratio serves as a measure of financial risk as it represents future additional payments that are expected to be disbursed due to the tendency component. The results have important implications for designing agricultural hedging instruments for coffee producers at an individual scale or as reinsurance instruments.

This article presents a novel methodology to assess the financial risk to crops in highly weather-volatile regions. We use data-driven methodologies that use singular value decomposition techniques in a low-income economy. The risk measure is first derived by applying data-driven frameworks, a Principal Component Analysis (PCA), and Singular Spectrum Analysis (SSA) to productive coffee crops in Colombia (163 weather stations) during 2010–2019. The objective is to understand the future implications that index insurance tools will have on strategic economic crops in the country. The first stage includes the identification of the PCA components at the country level. The risk measure, payouts-in-exceedance ratio, or POER, is derived from an analysis of the most volatile-weather-producing regions. It is obtained from a linear index insurance model applied to the extracted singular-decomposed tendencies through SSA on first-component data. The financial risk measure due to weather volatilities serves to predict the future implications of the payouts-in-exceedance in both seasons—wet and dry. The results show that the first PCA component contributes to forty percent of the total variance. The seasonal forecast analysis for the next 24 months shows increasing additional payouts (PO), especially during the wet season. This is caused by the increasing average precipitation tendency component with POERs of 18 and 60 percent in the first and second years. The findings provide important insights into designing agricultural hedging insurance instruments in low-income economies that are reliant on the export of strategic crops, as is the case of Colombian coffee.

This article is a discussion of the concept of index‐based agricultural insurance and the possible role of real options to reduce the basic risk. Indeed, to address the consequences of variability of weather within climate, experiments based on indexed agricultural insurance have been implemented in recent years. However, this locally defined insurance scheme has a weak point called the basic risk, i.e., the difference between the reality of climatic shocks and the payment of compensation. Real options allow this gap to be filled by offering alternatives to farmers. This article is the first to discuss the use of real options in the basic risk management of index‐based climate agricultural insurance. The implications for farmers in developing countries, insurers, and local and institutional organizations and communities are important: better management of operating conditions, optimized financial management, and consideration of real climatic conditions. [ABSTRACT FROM AUTHOR]

• Shows how Index-Based Agricultural Insurance echoes colonial interventions. • Links climate vulnerability to history of finance, labour and migration in Senegal. • Develops Marxian concept of 'latent' surplus populations. Amidst growing concern about the displacement of rural populations exposed to climate change, new financial instruments are increasingly being presented as key tools for the management of climate risks. Index-based agricultural insurance (IBAI) is a particularly key example. Recent critical work has pointed to the deeply neoliberal character of IBAI and like interventions. However, the promotion of new financial instruments in response to crises of agrarian production has a much longer history in Africa and elsewhere. This article draws on Marx's concept of 'latent' surplus populations to trace out and explain parallels between IBAI and colonial interventions in Senegal's groundnut basin. Approaching the question in this way, the article highlights the long-run historical co-production and interdependence of the Senegalese state and a political ecology of groundnut production in which relations of indebtedness and the exposure to variable rainfall of a fragile relative surplus population has often been crucial to the mobilization of cheap labour for groundnut production. IBAI is thus positioned as part of a recurrent trajectory of emergency financial interventions aimed at smoothing out the contradictions implicit in this socio-ecological configuration. [ABSTRACT FROM AUTHOR]

In Senegal, various development pilot projects experimented with agricultural index insurance to make drought insurable. These interventions produced 'rainfall deficit' as an environmental problem suited for such market-based solutions. Investigating the materiality of this index insurance scheme, I explore the environmental market infrastructure, which produces risk conventions, articulates governance and market requirements, and fuels the promise of cheap, efficient, and automated environmental risk management in the Global South. I show that the production of such risk requires both a selective reduction of the physical reality of drought and the substantial reordering of material activities that organize many actors around rainfall deficit. Meteorological data produced by rain gauges placed in Senegalese fields were a central element in the initial infrastructure of index insurance. However, as reductionist technologies are often prone to failure, this index insurance scheme met many challenges. After documenting the design of this insurance scheme and the obstacles encountered, the paper depicts how actors in charge of its implementation made a shift in the insurance infrastructure from field rain gauges to remote sensing – in order to re-energize index insurance's expectations. [ABSTRACT FROM AUTHOR]

We play a series of incentivized laboratory games with risk-exposed cooperative- based coffee farmers in Guatemala to understand the demand for index-based rainfall insurance. We show that insurance demand goes up as increasingly severe risk makes insurance payouts more partial (payouts are smaller than losses), but demand is ad- versely effected by more complex risk structures in which payouts are probabilistic (it is possible that a shock occurs with no payout). We use numerical techniques to esti- mate a flexible utility function for each player and consequently can put exact dollar values on the magnitude of the behavioral response triggered by probabilistic insur- ance. Exploiting the group structure of the cooperative, we investigate the possibility of using group loss adjustment to smooth idiosyncratic risk. Our results suggest that consumers value probabilistic insurance using a prospect-style utility function that is concave both in probabilities and in income, and that group insurance mechanisms are unlikely to solve the issues of low demand that have bedeviled index insurance markets.

Objective: this article studies the efficiency of a novel regression approach, the geographically weighted quantile lasso (GWQlasso), in the modeling of yield-index relationship for weather index insurance products. GWQlasso allows regression coefficients to vary spatially, while using the information from neighboring locations to derive robust estimates. The lasso component of the model facilitates the selection of relevant explanatory variables. Methodology: a weather index insurance (WII) product is developed based on one-month standardized precipitation index (SPI) derived from a daily precipitation dataset for 41 weather stations in the state of Paraná (Brazil) for the period from 1979 to 2015. Soybean yield data are also used for the 41 municipalities from 1980 to 2015. The effectiveness of the GWQlasso product is evaluated against a classic quantile regression approach and a traditional yield insurance product using the spectral risk measure (SRM) and the mean semi-deviation. Results: while GWQlasso proved as effective as quantile regression, it outperformed the yield insurance product. Conclusion: the GWQlasso is an alternative to the crop insurance market in Brazil and other locations with limited data.

The suitability of insurance products often depends greatly on individual circumstances. This paper examines the challenges of heterogeneity in a relatively new product, weather‐indexed insurance. This index insurance product has been launched in over a dozen countries, with the goal of enabling households engaged in agricultural activity a means to manage risk. Using data from a large‐scale field experiment, we build and calibrate a model which accounts for household investment decisions, including the scope for self‐insurance via labor markets to (risky) wage work. Our results show that insurance is most valuable to households with reduced access to wage labor, or to those who face wages that are sensitive to rainfall risk. These findings have important implications for areas where index insurance is most effective. [ABSTRACT FROM AUTHOR]