Index insurance is promoted as a low-cost approach to increasing access to formal insurance products in regions and for individuals that were previously inaccessible for conventional insurance products. These products are now used in multiple nations and by various humanitarian organizations to protect the vulnerable from the sometimes devastating impacts of weather related shocks. Those wishing to support the development or provision of these products generally turn to agronomists, meteorologists and/or remote sensing specialists to help them identify the most accurate and useful index for their products.
But, there is no consensus in these communities on which of the many off-the-shelf or pay-for-service indices most accurately track real-world outcomes. Furthermore, household preferences, such as the desire to meet basic needs or an aversion to extremely poor outcomes, make metrics that are commonly used to measure relationships (e.g., the mean error, correlations) less relevant when examining the quality of an insurance product.
This study uses economic approaches and the case of the index based livestock insurance (IBLI) product in Kenya to compare the quality of insurance products developed from a variety of satellite -based indices, all of which have either been proposed or are/have been used by insurance or insurance-like products in the region.
Although the indices are highly correlated to each other (ρ>0.98), a utility analysis provides insight into how the small differences can lead to larger differences in product quality. In addition, we examine an additional set of indices that aim to predict end of season conditions early in the season, finding that they do so accurately. More generally, this work provides guidance to those working to identify an appropriate index for their product and for index developers in the remote sensing community as they work to improve upon existing products.