For those developing satellite-based insurance products, there is no consensus in the scientific community on which of the many available indices most accurately track agro-ecological shocks as experienced by farmers and pastoralists. Furthermore, metrics commonly used by the remote sensing community for assessing the accuracy of indices in retrieving biophysical variables are insufficient in the case of insurance, because they do not consider the value of insurance coverage in terms of household welfare.
This study begins to fill this knowledge gap by bridging two index insurance literatures: the remote sensing science literature that focuses on the predictive power of indices, and the economic literature that focuses on welfare outcomes. The article uses a longitudinal panel of household survey data from Kenya to compare the quality of existing and potential insurance products. These products are developed from different processing chains applied to time series of the satellite-based Normalized Difference Vegetation Index (NDVI).
Although the indices are highly correlated to each other (ρ > 0.95), a utility analysis provides insight into how small differences can lead to larger differences in product value. Our results highlight that index accuracy, cost, and timeliness of payments must be considered jointly when assessing insurance quality for clients.