Fig. 22.1. Payout structure for a hypothetical rainfall contract traded in exchange markets, ttese exchange-traded contracts are used primarily by firms in the energy sector, although the range of weather phenomena that might potentially be insured using index contracts appears to be limited only by imagination and the ability to parameterize the event. A few examples include excess or deficient precipitation during different times of the year, insufficient or damaging wind, tropical weather events such as typhoons, various measures of air temperature, measures of sea surface temperature, the El Niño Southern Oscillation (ENSO) tied to El Niño and La Niña, and even celestial weather events such as disruptive geomagnetic radiation from solar flare activity. Contracts are also designed for combinations of weather events, such as snow and temperature (Dischel 2002; Ruck 1999).
tte potential for the use of index insurance products in agriculture is thus significant (Skees 2003). A major challenge in designing an index insurance product is minimizing basis risk. Basis risk refers to the potential mismatch between index triggered payouts and actual losses. It occurs when an insured has a loss and does not receive an insurance payment sufficient to cover the loss (minus any deductible) or when an insured has a loss and receives a payment that exceeds the amount of loss. Since index-insurance indemnities are triggered by exogenous random variables, such as area yields or weather events, an index-insurance policyholder can experience a yield or revenue loss and not receive an indemnity, tte policyholder may also experience no yield or revenue loss and still receive an indemnity, tte effectiveness of index insurance as a risk management tool depends on how positively correlated farm yield losses are with the underlying index. In general, the more homogeneous the area, the lower the basis risk and the more effective area-yield insurance will be as a farm-level risk management tool. Similarly, the more closely a given weather index actually represents weather events on the farm, the more effective the index will be as a farm-level risk management tool.
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