Increasing farmers’ adoption of agricultural index insurance: The search for a better index

Abstract:

The weather index insurance promises to provide farmers’ financial resilience when struck by adverse weather conditions, owing to its minimal moral hazard, low transaction cost, and swift compensation. Despite these advantages, the index insurance has so far received low level of adoption. One of the major causes is the presence of “basis risk”—the risk of getting an insurance payoff that falls short of the actual losses. One source of this basis risk is the production basis risk—the probability that the selected weather indexes and their thresholds do not correspond to actual damages. Here, we investigate how to reduce this production basis risk, using current knowledge in non-linear analysis and stochastic modeling from the fields of ecology and hydrology. We demonstrate how the inclusion of rainfall stochasticity can reduce production basis risk while identifying events that do not need to be insured. Through these findings, we show how much we can improve farmers’ adoption of agricultural index insurance under different design contexts.