Assessing the Sensitivity and Viability of Index Insurance as an Adaptation Tool in a Changing Climate Context: Case Study in the West African Sahel

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Wednesday, 5 February 2014: 9:30 AM
Room C101 (The Georgia World Congress Center )
Asher Siebert, Rutgers University, Piscataway, NJ; and N. Ward

Extreme climate events have significant adverse impacts on many sectors of society around the world, including the agriculture sector in the developing world. One of the ideas that has been explored to help address these risks and vulnerabilities is the concept of index insurance. Index insurance differs from traditional insurance in that payouts are made on the basis of a geophysical index directly measuring an environmental condition, rather than through a loss claim and verification procedure. As a consequence of this simpler framework that can expedite payouts, index insurance may have practical potential in a developing world context where traditional property or agriculture insurance markets tend to be limited or nonexistent. This work will focus on the exploration of theoretical index insurance contracts in the West African Sahel nations of Niger, Burkina Faso and Mali.

Climate related index insurance in Africa has a number of key non-climate related challenges including risk communication, establishing trust with the potential client population and technical limitations of index insurance contracts. However, beyond those challenges, the changing climate itself induces a change to the underlying basis climate risk by altering the frequency of threshold crossing extreme events (hereafter TCEs) that would trigger insurance payouts.

This study explores the sensitivity and viability of such a model index insurance scheme in the West African Sahel in the context of a changing climate in the 2014-2040 period. The theoretical index insurance contracts are envisioned as national-scale contracts for Niger, Mali and Burkina Faso. Agricultural data to inform the index insurance models are taken from the Food and Agriculture Organization (FAO), although they may be supplemented by some provincial agricultural data. The theoretical index insurance framework has two thematic components: a component targeted towards irrigated rice farmers along the River Niger and its tributaries and a component targeted towards the millet crop of subsistence rain-fed farmers. The component targeted towards the irrigated farmer population focuses on flooding risk using streamflow data from the Niger Basin Authority and the component targeted towards the subsistence farmers focuses on drought risk using satellite and station rainfall data. Vegetation, water stress and/or temperature indices may also be considered for the subsistence farmer component. However, preliminary analysis shows that robust index insurance contracts can be constructed on the basis of station rainfall from the Global Historical Climate Network (GHCN), the gridded station rainfall from the NOAA Precipitation over Land (PRECL) dataset and from the merged station-satellite rainfall from the Global Precipitation Climatology Project (GPCP). Preliminary analysis shows that millet production, especially in Niger and Burkina Faso correlates well to seasonal precipitation especially the GHCN and PRECL rainfall estimates.

The methodology for exploring the future TCE frequency will borrow significantly from two prior publications. Monte Carlo simulations will be employed to model TCE frequency under a range of assumptions about the trend, decadal variability and temporally evolving shape of the index distributions. These prior studies along with supporting climate literature have found that the TCE frequency and the range of outcomes are sensitive to proposed changes in the mean and to levels of multi-decadal variability consistent with the IPCC and with other regional climate literature. Furthermore, the coefficient of variation is found to play a significant role in determining the frequency of TCEs. Assumptions about the regional trend in rainfall and streamflow will also be informed by the climate modeling literature and by several GCM datasets.

Since the TCE frequency will correspond, in the index insurance model, to the frequency of payouts, this issue has direct bearing on the financial viability/solvency of such an index insurance contract over time in the context of a changing climate. Some responses can be adopted to limit the threat to financial viability, such as by using temporally evolving thresholds. Further, by framing a contract as proposed, to address anti-correlated flood and drought risks concurrently for different populations, the probability of concurrent payouts to both client populations is reduced.

However, these benefits noted, the strong multi-decadal nature and uncertain trend of the region's rainfall and streamflow characteristics will likely pose challenges to the long-term viability index insurance. Given the high level of recent rains and the incidence of riverine flooding in recent years, flooding risk appears to be the greater concern for the most immediate future.