Index Based Livestock Insurance (IBLI) 01
Hello, my name is Munenobu Ikegami. This is my first essay in English in this forum. I have worked for Index Based Livestock Insurance (IBLI) project from September 2008 to February 2018 at International Livestock Research Institute (ILRI) and I would like to review what we learned in this essay series.
Pastoralists in Northern Kenya and Southern Ethiopia face drought and associated risks that are large in magnitude (frequently causing a 20-40% livestock mortality rate) and frequent (once every 4-5 years). ILRI and its research and implementation partners launched a commercial IBLI product in January 2010 in an effort to mitigate the negative consequences of livestock mortality risk. Research on IBLI can be divided into three groups: 1) insurance design; 2) insurance uptake; and 3) insurance impacts. In this essay I will review 1) insurance design.
Chantarat et al. (2013) explains the design. What we would like to insure is the negative economic shock due to drought and livestock mortality. Livestock is the second largest productive asset the pastoralists have following their own human capital. When drought occurs, all of forage and water for livestock, livestock milk production, birth rate would decrease and livestock mortality would increase. Note that decreased livestock herd size due to decreased birth date and increased mortality rate affect the pastoralists negatively even in the following seasons after the drought.
Traditional insurance for livestock mortality would not be commercially viable due to large transaction costs due to that pastoralists are herding livestock in remote and large space and it is difficult to verify each animal’s death by a insurance company. Index insurance can overcome these problems. Instead of making indemnity payout based on each animal’s death like traditional insurance, index insurance makes indemnity payout based on an index which represents average loss in a region. IBLI applies this idea to livestock mortality due to droughts in the region.
Index should have the following properties: 1) closely related with the loss to be insured; 2) not manipulated; 3) available timely; 4) constructed with low costs. The index Chantarat et al. (2013) provides is predicted livestock mortality based on Normalized Difference Vegetation Index (NDVI). NDVI is measurement on how green earth surface is based on satellite. Chantarat et al. (2013) shows that NDVI can explain livestock mortality due to droughts in the area in the past well and suggests to use predicted livestock mortality based on NDVI as the index for IBLI.
In the next essay, I will continue reviewing the design of IBLI.
(Author: Munenobu Ikegami)
Reference
Chantarat, Sommarat, Andrew G. Mude, Christopher B. Barrett, and Michael R. Carter. 2013. “Designing Index-Based Livestock Insurance for Managing Asset Risk in Northern Kenya.” Journal of Risk and Insurance. Vol. 80, No. 1, pp. 205-237.