Index-based Insurance Product Research Articles

Integrating rainfall index-based insurance with optimal crop management strategies can reduce financial risks for Australian dryland cotton farmers

Drought undermines the financial sustainability of farmers. While farmers have adopted various strategies to mitigate some drought impacts, they remain exposed to substantial drought risk. Insurance could be useful in managing climatic risks and for encouraging farmers to take sensible risks (e.g., changing their sowing date to increase yield), but it can be costly. Here, we tested whether the integration of a change in sowing date with rainfall index-based insurance could improve farmer profitability and income stability. We used the Agricultural Production Systems Simulator (APSIM)-Cotton model to simulate cotton lint yields for various sowing dates, taking into account different management strategies, across three dry-land cotton research farm sites – Dalby, Goondiwindi, and Theodore – from 1940 to 2022. We designed the index-based insurance payout when the average rainfall received during the growing season falls below a predefined level, such as the 5th, 10th, or 20th percentile of rainfall. Our study, which involved 3.9 million cotton lint simulations and 3,000 rainfall index-based insurance products, showed that combining a shift in sowing date with insurance can lead to an income improvement of up to 21.5% at some study sites. Additionally, in drought years, the income improvement for farmers who combined optimal sowing dates with rainfall index-based insurance was up to 48.0%. The framework developed in this study could aid in devising financial strategies to enhance farming resilience during climate extremes.

Does the Mutton Sheep Weather Index Insurance Promote the Mutton Sheep Industry?A Study based on the Endogenous Switching Regression Model

In 2018, as the first livestock weather index-based insurance product for grassland animal husbandry, the mutton sheep weather index insurance was officially listed as a subsidy agricultural insurance by the Government of the Inner Mongolia Autonomous Region, which was later in 2019 implemented throughout the XilinGol League of the autonomous region. Employing the endogenous switching regression model, this study investigates the factors influencing herdsmen's purchasing decisions, as well as the impact of mutton sheep weather index insurance on the mutton sheep industry scale, which are accomplished based on 308 survey data from herdsmen in the XilinGol League. The empirical results reveal that the age, age squared, pasture area and neighbors' purchasing intention constitute the significant influencing factors of the herdsmen's purchasing decisions, while the pasture area and net pastoral income affect the scale of mutton sheep farming prominently. Furthermore, according to the ATT results, the mutton sheep weather index insurance produces an insignificant impact on the sheep farming scale of herdsmen. The conclusions of this study suggest that the mutton sheep weather index insurance is not contrary to the cattle-increasing, sheep-reducing policy in the Inner Mongolia Autonomous Region, which also provide a solid theoretical basis for the promotion of the insurance throughout the autonomous region.

Is Weather Index Insurance Sufficient for Smallholder Protection? Emerging Insights from Rainfall-Index Calibration of Maize Crop Losses in Central-West Nigeria

Residual impacts from rainfall deficit and failures of traditional crop insurance to protect smallholders are resulting in economic losses threatening Post-Paris adaptation target in Nigeria. Weather index insurance is being considered as a possible pathway towards sharing farmers’ risks. This paper analyzed the reliability of rainfall indexes as proxy for calibrating grain crop losses in designing index-based insurance product for farmers in Central-West Nigeria. Results reveal that two strongest correlated rainfall indexes in the development phase of maize are the second dekad cumulative rainfall climatology and cumulative rainfall below the pre-set 440mm threshold, however it was the third dekad cumulative rainfall climatology and consecutive dry days of total rainfall < daily 2.5 mm threshold in the reproductive stage. There is an overall weak statistical relationship between maize yield and rainfall indexes calibrated in middle savannah belt of Nigeria. This study provides a firsthand empirical validation that rainfall-based indexes are though fairly promising but not sufficiently measure actual farmers’ income losses, hence should not be regarded as a standalone safety-net for protecting smallholders. Careful consideration is required in developing appropriate weather indexes for designing index-based insurance product that will fully captured food crop losses significantly attributed to rainfall deficits, thus facilitate uptake in the semi-arid savannah zone of Nigeria.

Adoption and preferences for coffee drought index-based insurance in Uganda

Micro-insurance can be an effective approach to smoothening income in adverse times and potentially a way to contribute to the financial inclusion of vulnerable populations. However, direct sales to individual smallholders remains a challenging task without an easily scalable solution. The current research seeks to find the determinants of adoption of a stand-alone coffee index-based insurance product in Uganda marketed by a farmer cooperative, and elicited preferences for improving the design and delivery model. A stratified household survey was conducted among 614 farmers, of which 40% adopted insurance and 62% were member of a farmer cooperative. In odds ratio terms, adopters perceived themselves to be 3.09 times more likely to receive a pay-out than non-adopters (P

Incorporating Climate Change Projections into Risk Measures of Index-Based Insurance

We use regional climate model projections to quantify long-term projected changes to risk measures for an example set of temperature index–based insurance products in California. This region is a major agricultural producer for the United States and the world. The climate model projections are an ensemble of six regional climate model runs obtained from the North American Regional Climate Change Assessment Program. Hindcasts for the period of 1971–2000 are compared to historical observed temperature data for bias and variance corrections. Adjusted future model projections are used to estimate distributions of cooling degree days for 2041–2070, which are then used to estimate risk measures for index-based insurance products to demonstrate the scale of changes that climate models project through mid-century in actuarial terms. More broadly, this article provides an illustration of the use of climate data products to explore actuarial risks.

Parametric crop insurance against floods: The case of Bosnia and Herzegovina

The importance of risk management in agriculture is unquestionable. Farmers in Bosnia and Herzegovina face weather, product, and price and market risk. Index-based insurance products for agriculture present alternatives for managing weather risk. They differ from classical insurance products in that they do not remunerate actual loss and to purchase a weather index insurance policy the insured does not actually have to have an insurable interest. In this research, two flood parametric insurance products are presented, one with fixed compensation and the other with compensation proportional to flood intensity.

COPULA-BASED STATISTICAL MODELLING OF SYNOPTIC-SCALE CLIMATE INDICES FOR QUANTIFYING AND MANAGING AGRICULTURAL RISKS IN AUSTRALIA

COPULA-BASED STATISTICAL MODELLING OF SYNOPTIC-SCALE CLIMATE INDICES FOR QUANTIFYING AND MANAGING AGRICULTURAL RISKS IN AUSTRALIA

Mitigating risk for floodplain agriculture in Amazonia: a role for index-based flood insurance

ABSTRACT The fertile floodplain of the Amazon river offers considerable potential for agriculture, yet it is a risk-filled environment with heightened vulnerability due to climate change. The annual flood pulse deposits nutrient-rich sediment on the floodplain enabling increased agricultural productivity during the low water season. However, crops growing on the floodplain are at high risk of loss due to flood dynamics. Drawing on data from household surveys (n = 83), focus group discussions, and key informant interviews, this study assesses potential flood risk mitigation tools for floodplain rice farmers along the Amazon river near Iquitos, Peru. Farmers’ risk mitigation preferences are explored through willingness to pay (WTP) methods for flood-tolerant rice varieties, river information services, and index-based flood insurance. Results indicate that measured ambiguity aversion is a key driver in the decision to mitigate flood risk. The study suggests that the environmental risk context may be appropriate for an index-based flood insurance product, and farmers and local institutions see the promise of flood insurance. With climate change scenarios predicting greater variability in the flood regime, mitigating flood risk is paramount to reducing the vulnerabilities and unlocking opportunities for floodplain farmers in Amazonia.

Copula statistical models for analyzing stochastic dependencies of systemic drought risk and potential adaptation strategies

Development and implementation of advanced statistical models for analyzing stochastic dependencies of systemic weather risk can help farmers, agricultural policy-makers and financial agents to address potential risk adaptation strategies and mitigation of threats to the agricultural industry. This study develops copula-based statistical models to provide a better understanding of systemic weather risks with agricultural and weather event data from Australia. In particular, we adopt a C-vine approach to model the joint insurance losses caused by drought events occurring simultaneously across different locations, and consecutively in different growing seasons. This modelling approach is enriched by a clustering analysis process through the multidimensional Kruskal–Shephard scaling method. Daily rainfall data (1889–2012) recorded in sixteen meteorological stations across Australia’s wheat belt spanning different climatic conditions are employed. On a regional scale, droughts occurring in the west are more scattered during the October–December period and for April–June and October–December in the eastern, south-eastern and southern regions. On a national scale, drought events in the east are likely to spread out to the south-east and the south but not to the west. The results also reveal that the drought events in different seasons may not be perfectly correlated. Therefore, we conclude that spatial and temporal diversification strategies are likely to feasibly reduce the systemic weather risk in Australia. In particular, the average risk-reducing effect of the entire insured area across regional, national and temporal scales ranges between 0.62–0.94, 0.48–0.76, and 0.25–0.33, corresponding to 5%- (extreme drought) and 25%-quantiles (moderate drought). The findings suggest that diversifying risks over time is potentially more effective than spatial diversification. The outcomes may also act as an efficient tool for agricultural risk reduction, but simultaneously, it may also provide immensely useful information for suitable pricing of weather index-based insurance products.

ENSO Index-Based Insurance for Agricultural Protection in Southern Peru

Agricultural operations in southern Peru are particularly vulnerable to climate variability due to water resource scarcity. In general, the response to drier than normal conditions in this region is reactive and fairly limited due to challenges associated with climate forecasting and administrative capacity to distribute resources. To shift this paradigm, we investigate the potential for an El Niño–Southern Oscillation index-based insurance product. The article presents a demonstration of methodology and application for one specific crop in a department of southern Peru. The purpose of this product is to streamline the ability of decision makers to provide financial relief to affected farmers during, and perhaps before, drought; extending the lead-time of the index that is used to trigger product payouts produces results of similar skill to a product trained on concurrent conditions. Issues explored in this work include basis risk, initial endowment requirements, product longevity, and the potential crossover from index-based insurance to forecast-based financing. The ability of such products to mitigate losses during and after drought may be advantageous in Peru and other regions with notable interannual climate variability.

Cash transfers and index insurance: A comparative impact analysis from northern Kenya

Cash transfers and index insurance have become popular interventions by development agencies worldwide, yet surprisingly little is known about these programs' comparative impacts on participant behavior or well-being. This paper exploits exogenous variation in program participation and panel data from Kenya to compare the causal impacts of a cash transfer program (HSNP) and an index-based insurance product (IBLI), which were implemented contemporaneously among the same population. We find that both programs benefit clients. HSNP improves child health, as measured by mid-upper arm circumference (MUAC), and helps households maintain their mobility-dependent livestock production strategies. Households with IBLI coverage make productivity increasing investments, reduce distress sales of livestock during droughts, and see a marked increase in income per adult equivalent. Estimating the impacts per total program costs reveals that the two programs perform comparably on average, while IBLI's impacts per unit marginal cost are considerably larger than HSNP's.

Index Based Insurance for Landslide Risks in Nepal

Landslide is one of the major hazard in Nepal resulting annual loss of more than 50 million Nepalese Rupees. Almost all of the landslide are caused by rainfall and occur during the monsoon season. Like other weather induced disasters, landslide risks are also need a significant resources to mitigate the risks as well as to recover the damages. One of the key issues in local DRM planning process is the financing risk reduction, preparedness and response activities, as the local agencies have very limited fund under their disposal to spend for disaster risk management. Tapping the private sector resources has been on the book however, very little or no has been realized. In this context this paper analyses feasibility of an index-based insurance product to finance landslide risks management processes in the hilly reason of Nepal. The study finds that taking the rainfall threshold, developed for early warning system as a trigger point, it is possible to develop an index-based insurance product, which will provide indemnities based on the rainfall data from a nearby weather stations. It is also assessed that a premium of around 12% of the insurance amount is also feasible for the insurance product. For financing, this paper suggests to a pool fund managed by the network of villages with reinsurance options through national or international reinsurance companies.

Assessing the Challenges in Successful Implementation and Adoption of Crop Insurance in Thailand

The purpose of this paper is to assess the gaps in the adoption of crop insurance in Thailand and suggest possible solutions relating to policy support and framework, implementation mechanisms, technology adoption, and awareness amongst farmers. The methodology includes a literature review, interaction with officials, rice experts and insurance experts, and discussion with farmers. A study was undertaken at province level to assess the impact of using rainfall index as a threshold. Additionally, focused group discussions (FGD) were conducted with rice farmers at the village level. Key issues targeted in the FGD were to understand the behavior and practices during droughts, impact of drought on crop yield, methods already in use to reduce the impact, such as plantation of drought-resistant rice, and the adoption of crop insurance. Data availability is a challenge and has led to withdrawal of Weather Index Insurance (WII) in 2015. WII have threshold levels based on historical rainfall. Adoption of coping mechanisms, such as drought-resistant rice and irrigation increases the chances of adverse selection. In absence of ground based weather data, a combination of satellite agriculture drought information can be used to make crop insurance more attractive as it would help in reducing basis risk and improving insurers and farmers’ confidence in the product. Discussion with farmers, insurance companies, and the Bank of Agriculture and Agricultural Cooperatives (BAAC) in Thailand suggested low awareness among farmers about the potential benefits of weather index insurance products. Relatively low compensation is also an obstacle. Proper marketing and awareness raising campaigns should also accompany the introduction of index-based insurance products.

Microinsurance Decisions: Gendered Evidence from Rural Bangladesh

Most index-based insurance products have been developed without giving explicit attention to gender. However, there is ample of evidence that shocks affect men and women differently and that they allocate resources in different ways. In Bangladesh, it is often assumed that women are less involved in agriculture, and, therefore, agricultural insurance might not be of interest to rural women. However, this assumption has not been tested in the field. This article draws from a field research experiment to examine the gendered aspects of willingness to pay for index-based insurance in Bangladesh. Participants were presented with risky lotteries and a specific insurance contract and were asked to choose how much, if any, of the insurance they wanted to buy at a given price. The probability structure, whether the risk was catastrophic or moderate and whether there was high or low basis risk, varied within sessions. The price of the insurance varied across sessions. Each participant was also given a short questionnaire, which collected information on the demographic characteristics, risk preferences, agricultural risks, knowledge of insurance products, and asset ownership. In the study, 97 percent of the participants decided to buy agricultural insurance, with no significant differences between men and women, even though women were less involved in agricultural decision-making. We found a small decrease in take-up for the low-probability event, driven by the women in the sample. When we examined the number of units bought, we found that men were likely to buy more units than women. Total wealth, as captured by total land owned, had no effect on the units bought. However, among women, total wealth mattered and had a positive correlation. Finally, we found that women had less education and lower financial literacy than their male counterparts, and did not have the experience possessed by men to understand agricultural risks. It placed them at a disadvantage when making insurance purchase decisions.

Validation of a Forage Production Index (FPI) Derived from MODIS fCover Time-Series Using High-Resolution Satellite Imagery: Methodology, Results and Opportunities

An index-based insurance solution was developed to estimate and monitor near real-time forage production using the indicator Forage Production Index (FPI) as a surrogate of the grassland production. The FPI corresponds to the integral of the fraction of green vegetation cover derived from moderate spatial resolution time series images and was calculated at the 6 km × 6 km scale. An upscaled approach based on direct validation was used that compared FPI with field-collected biomass data and high spatial resolution (HR) time series images. The experimental site was located in the Lot and Aveyron departments of southwestern France. Data collected included biomass ground measurements from grassland plots at 28 farms for the years 2012, 2013 and 2014 and HR images covering the Lot department in 2013 (n = 26) and 2014 (n = 22). Direct comparison with ground-measured yield led to good accuracy (R2 = 0.71 and RMSE = 14.5%). With indirect comparison, the relationship was still strong (R2 ranging from 0.78 to 0.93) and informative. These results highlight the effect of disaggregation, the grassland sampling rate, and irregularity of image acquisition in the HR time series. In advance of Sentinel-2, this study provides valuable information on the strengths and weaknesses of a potential index-based insurance product from HR time series images.

Development of an index-based insurance product: validation of a forage production index derived from medium spatial resolution fCover time series

An index-based insurance is being developed to estimate and monitor forage production in France in near real-time based on a forage production index (FPI) derived from the fraction of green vegetation cover (fCover) integral, obtained from medium spatial resolution time series. This article presents the first step of the scientific validation implemented. The grassland parcels, the field protocol established to collect biomass production data, and the method used to get the fCover are described. Local ground measurements of biomass production are compared with FPI values obtained from high-resolution space-based images. Discrepancies between the two variables are quantified by the coefficient of determination, the mean square error and the normalised root mean square error. First, fCover derived from the four sensors are coherent demonstrating the ability of the algorithm used to provide a consistent way of calculating fCover. Second, for the whole data set, the scatter plot between FPI and biomass shows an acceptable correlation (R2 = 0.75) improved when only taking into account data recorded up until the production maximum (R2 = 0.81). Third, the analysis carried out on the scale of the parcels, grass species, period of mowing or climatic conditions reveals variability on the regression coefficients indicating that other explanatory variables should be integrated to better compute the FPI.

Hedging effectiveness of weather index-based insurance in China

Purpose – Maize production in China is exposed to pronounced yield risks, in particular weather risk, which is one of the most important and least controllable sources of risk in agriculture. The purpose of this paper is to analyze the extent to which weather index-based insurance can contribute to reducing the revenue risk in maize production caused by yield variations. An average farm producing maize is analyzed for each of eight Chinese provinces, six of which are part of the Northern Plains of China. Design/methodology/approach – Data are based on the Statistical Yearbook of China and the Chinese Meteorological Administration. The used method of insurance pricing is burn analysis. Hedging effectiveness of precipitation index-based insurance is measured by the relative reduction of the standard deviation (SD) and the Value at Risk of maize revenues. Findings – Results reveal that precipitation index-based insurance can cause a reduction of up to 15.2 percent of the SD and 38.7 percent of the Value at Risk with a 90 percent confidence level of maize revenues in the study area. However, there are big differences in the hedging efficiencies of precipitation index-based insurance measured at different weather stations in the various provinces. Therefore, it is recommended for insurance providers to analyze the hedging effectiveness of weather index-based insurance with regard to the geographical location of their reference weather station if they would like to offer weather index-based insurance products. Research limitations/implications – The absence of individual, long-term yield data in the study area prevents the evaluation of risk on individual farms. Thus, the hedging effectiveness can only be analyzed on an aggregated level of yield data and can rather be modeled for an average farm of a particular province. Originality/value – To the author's knowledge, this paper is the first that investigates the hedging effectiveness of precipitation index-based insurance designed for reducing revenue risk of maize production in eight Chinese provinces.

The Insurability Framework Applied to Agricultural Microinsurance: What Do We Know, What Can We Learn?

Agricultural microinsurance has gained increasing attention over the last years. In light of climate change, changing weather trends and more repeatedly occurring natural disasters, a wave of innovative approaches to insuring agricultural production risks, particularly index-based insurance products, have been proposed and implemented. However, the results of many of these projects were disappointing, raising the question whether microinsurance could provide viable coverage for agricultural production risks at all. This paper reviews existing theoretical and empirical research on the feasibility of agricultural microinsurance and discusses different approaches to cover agricultural productions risks. It finds that, contrary to common beliefs, many agricultural production risks, including drought, hail, floods and livestock diseases, could be effectively covered by microinsurance, although not all by index-based approaches. It makes the case for a flexible combination of different approaches to microinsurance, such as community-based and group insurance, with technological advancements such as remote-sensing techniques and index insurance.

Index Based Livestock Insurance for Northern Kenya’s Arid and Semi-Arid Lands: The Marsabit Pilot

In Kenya’s arid and semi arid lands (ASALs), drought is the most pervasive hazard, natural or otherwise, encountered by households on a widespread level. This is especially true for northern Kenya, where more than 3 million pastoralist households are regularly hit by increasingly severe droughts. In the past 100 years, northern Kenya recorded 28 major droughts, 4 of which occurred in the last 10 years. For livelihoods that rely solely or partly on livestock, the resulting high livestock mortality rate has devastating effects, rendering these pastoralists amongst the most vulnerable populations in Kenya. As the consequences of climate change unfold, the link between drought risk, vulnerability and poverty becomes significantly stronger.Index-based insurance products represent a promising and exciting innovation for managing the climate related risks that vulnerable households face. The creation of insurance markets for events whose likelihood of occurrence can be precisely calculated and associated to a well defined index is increasingly being championed as a way to make the benefits of insurance available to the poor. Over the past year, the International Livestock Research Institute (ILRI), in collaboration with its partners at Cornell University, the BASIS Research Program at the University of Wisconsin-Madison, and Syracuse University, has pursued a substantial research program aimed at designing, developing and implementing market-mediated index-based insurance products to protect livestock keepers - particularly in the drought prone ASALs – from drought-related asset losses.Much of the initial preparatory phase, which included an extensive program of field work and stakeholder consultation, is now complete. An index-based livestock insurance (IBLI) contract has also been modeled, priced, and is ready for implementation. The remainder of this note defines the key features of a general index-based contract, highlighting the specifics of our IBLI contract, and lays out a pilot strategy to test its effectiveness and commercial sustainability.

Food Crop Farmers’ Willingness to Participate in Market-Based Crop Insurance Scheme: Evidence from Ghana

The study assesses food crop farmers’ willingness to participate in market-based crop insurance scheme in the Kintampo North Municipal of Ghana, using primary data solicited from 120 farmers in April 2010. The study employed descriptive statistical techniques to analyze the social, economic, demographic characteristics of farmers as well as their current risk management practices. Further, farmers’ willingness to participate in a hypothetical market-based insurance scheme was estimated using the contingent valuation method. The results reveal that the mean willingness to pay premium for a hypothetical loss of GH¢ 1,000 of farm income is GH¢24.43. The minimum and maximum willingness to pay premium, in the insurance scheme are GH¢5.00 and GH¢80.00 respectively. The empirical results of the Binary Logit Model reveal that farm size, family size and diversification via livestock are factors that influence farmers’ willingness to participate in crop insurance. Recommendations drawn for consideration by Government of Ghana (Ministry of Food and Agriculture), policy makers, insurance companies, development organizations and non-governmental organizations in rural poverty reduction are that the design and implementation of any crop insurance scheme in the Kintampo North Municipality and areas with similar characteristics should consider critical factors such as family size, farm size and livestock activities in the design. Further, a weather index-based insurance product should be piloted especially for droughts and floods while considering the current risk-management strategies employed by farmers. It is imperative that the Government subsidizes this program in the initial stages to encourage participation in the form of providing weather station equipment that would enable insurance companies to effectively validate liability claims by farmers.