Abstract
Abstract Rainfall is an important source of covariate shock in developing countries. Insurance against a rainfall index has, therefore, held much promise as a formal insurance product to protect the livelihoods of poor farmers. But how good is rainfall as a measure of covariate shocks? The imperfect association between them has been flagged as a reason for low demand for index insurance. Using district crop yields and rainfall data for India, we find that tail dependence characterizes the association between aggregate crop yields and rainfall. Could this property be exploited to design catastrophic loss insurance programs that have low basis risk? Using simulations of the estimated copulas, we show that the value of index-based insurance relative to actuarial cost is higher for insurance against extreme losses (of the index) than for insurance against all losses. We conclude that index insurance could find greater acceptability if it only insured extreme losses.
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