The Potential for Scale and Sustainability in Weather Index Insurance

THE POTENTIAL FOR SCALE AND SUSTAINABILITY IN WEATHER INDEX INSURANCE
FOR AGRICULTURE AND RURAL LIVELIHOODS
large investments in multi-peril crop insurance (MPCI) in 2006, 6 significantly
subsidizing the premium, which could undermine the further development of index
insurance. However, as the implementation of MPCI entails several challenges, index
insurance could be used to complement the MPCI policies and facilitate the
Government’s wider risk-management efforts (Case Studies 2 and 4).
Contract design and basis risk
Designing index insurance contracts is extremely complex, in part due to the effort
required to identify a weather index that correlates highly with agricultural loss and
thus minimizes basis risk. As mentioned earlier, basis risk is the potential mismatch
between the index-triggered payouts and the actual losses suffered by the policy
holder. With index contracts, it is possible for policyholders to receive a payout even
when they have suffered no losses, and conversely, policyholders may not receive a
payout when they have suffered a loss. Moreover, an individual farmer with rainfall
insurance could lose her crop to drought and not receive an indemnity if the drought
is not recorded at the reference weather station. The diversity of microclimates often
found within relatively small geographic areas means that basis risk is an inherent and
widespread problem.
There are a number of ways to reduce this risk. One is to limit the insurance to the
kinds of low-frequency, highly covariate weather risks that impact most people in a
region. Individual losses are then much more likely to be highly correlated with the
insured weather station event. This approach works best for disaster-relief index
insurance. It can also work for development index insurance, with the understanding
that alternative arrangements would be needed to help households manage more
frequent, less covariate risks.
Another approach is to identify weather indices that minimize basis risk for as
many households as possible in a region. Recent developments in crop-weather
modelling, as well as participatory approaches to the design of insurance contracts,
have demonstrated the potential to reduce basis risk, but the cost of developing these
indices can be high. They are also unlikely to transfer from one small region to
another, which makes scaling up more difficult and costly.
Basis risk can also be reduced by increasing the number and distribution of weather
stations in order to better capture spatial variation in climatic conditions when
writing contracts. However, adding weather stations can be costly (both to set up and
maintain), and new stations have no site-specific historical record.
Lack of historical data can sometimes be overcome by using existing records in the
proximity of the new station, in combination with remote sensing data, to create
‘synthetic’ and triangulated data sets for the new station. There is also interest in new
6 MPCI products are based on shortfalls of expected yield, not the damage caused by a particular event. They use
a farmer’s yield history as a baseline, and the shortfall is determined either on an area basis or for each individual
farmer. Usually the insured yield is 50-70 per cent of the farmer’s historical average yield.
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