Weather index-based insurance in a cash crop regulated sector: ex ante evaluation for cotton producers in Cameroon

In the Sudano-sahelian zone, which includes Northern Cameroon, the inter-annual variability of the rainy season is high and irrigation is scarce. As a consequence, bad rainy seasons have a massive impact on crop yield. Traditional insurances, which would mitigate such impact, suffer from asymmetric information. They are based on crop damage assessment leading to high transaction costs compared to the value of production. Moreover the important spatial variability of weather creates a room for pooling the impact of bad weather using index-based insurance products. We assess the risk mitigation capacity of weather index-based insurance for cotton growers. We compare the capacity of various indices, mainly based on daily rainfall, coming from different sources to increase the expected utility of a representative risk-averse farmer. We first give a tractable definition of basis risk and use it to show that weather index-based insurance is associated with large basis risk. It thus has limited potential for income smoothing (in accordance with previous results in Niger), whatever the index or the expected utility function is chosen. Using observed cotton sowing dates significantly decreases the basis risk of indices based on daily rainfall data. Second, in accordance with the existing agronomical literature we found that the length of the cotton growing cycle is the best performing index considered. Third, cutting the Cameroonian cotton zone into more homogeneous rainfall zone seems necessary to limit subsidisation of the driest zones. As a conclusion, we found very low gains to implementing an index insurance for cotton growers in Northern Cameroon: about 1% of certain equivalent income with standard utility functions. This is low, especially when compared to the price hedging (against seasonal variability of international prices) of the national cotton company by fixing cotton purchasing price before sowing. Such results could help for the design of an insurance for the zones for which production is heavily depending on meteorological factors, but also to take into account other determinants of profit variations, such as the cotton purchasing price.