This paper describes a novel effort at developing index-based insurance for locationaveraged livestock mortality as a means to fill an important void in the risk management instruments available to protect the main asset of pastoralists in the arid and semi-arid lands of Kenya, where insurance markets are effectively absent and uninsured risk exposure is a main cause of the existence of poverty traps. We describe the detailed methodology in designing such insurance contract with the underlying index uniquely constructed off explicit statistical predictions established using longitudinal observations of household-level herd mortality, fit to high quality, objectively verifiable remotely sensed vegetation data not manipulable by either party to the contract and available at low cost and in near-real time. The resulting index performs very well out of sample, both when tested against other complementing household-level herd mortality data from the same region and period and when compared qualitatively with community level drought experiences over the past 27 years. We describe contract pricing and potential risk exposures of the underwriter using a rich time series of satellite-based vegetation data available from 1982-present. And finally, implementation opportunities and challenges are discussed to spur the product's pilot potential.

The number of index insurance pilots in developing countries has grown tremendously in recent years, but there has been little progress in our understanding of the quality of those products. Basis risk, or remaining uninsured risk, is a widely recognized but rarely measured feature of index insurance product quality. This article uses eight semi‐annual seasons of longitudinal household data to examine the distribution of basis risk associated with an index‐based livestock insurance (IBLI) product in northern Kenya. We find that IBLI coverage reduces exposure to covariate risk due to large shocks and mitigates downside risk substantially for many households, even at commercial premium rates. But index insurance is no magic bullet; insured households continue to face considerable basis risk. Examining the components of basis risk, we find that IBLI reduces exposure to covariate risk due to high loss events by an average of 63%. The benefits of reduced covariate risk exposure are relatively small, however, due to high exposure to seemingly mostly random idiosyncratic risk, even in this population often thought to suffer largely from covariate shocks. The result is that IBLI policyholders are left with an average of 69% of their original risk due to high loss events. This research underscores the need for caution when promoting index insurance as a risk mitigation tool, as well as the importance of product quality evaluation.

Basis risk -the remaining risk that an insured individual faces -is

No abstract

No abstract

No abstract

More than 400 million people in the developing world depend on dryland agriculture for their livelihoods. Dryland agriculture involves a complex combination of productive components: staple crops, vegetables, livestock, trees and fish interacting principally with rangeland, cultivated areas and watercourses. Managing risk and enhancing productivity through diversification and sustainable intensification is critical to securing and improving rural livelihoods. The main biophysical constraints are natural resource limitations and degradation, particularly water scarcity and encroaching desertification. Social and economic limitations, such as poor access to markets and inputs, weak governance and lack of information about alternative production technologies also limit the options available to farmers. Past efforts to address these constraints by focusing on individual components have either not been successful or are now facing a declining rate of impact, indicating the need for new integrated approaches to research for development of dryland systems. This article outlines the characteristics of such an approach, integrating agro-ecosystem and livelihoods approaches and presents a range of empirical examples of its application in dryland contexts. The authors draw attention to new insights about the design of research required to accelerate impact by integrating across disciplines and scales.

No abstract