Date & Hour: 29 May 2019, 4:00 pm

Venue: Seminar Hall 1

Title: Basis Risk in Index Insurance: Lower Tail Dependence and the Demand for Weather Insurance

By: Dr. Digvijay Singh Negi, Indian Statistical Institute, New Delhi.

Abstract: For a variety of reasons, agricultural insurance programs use losses against an index (rainfall, area yield) rather than losses against individual yields to make payouts. While this facilitates the supply of insurance, the resulting basis risk reduces the value of insurance and therefore reduces demand for it. Using district crop yields and rainfall data for India, we find that the association between crop yields and rainfall index is characterized by the statistical property of ’tail-dependence’. This implies that the associations between yield losses and index losses are stronger for large deviations than for small deviations. Or, basis risk is least for large deviations of the index. Using simulation we show that value to a risk averse farmer of index-based insurance relative to actuarial cost is highest for insurance against extreme or catastrophic losses (of the index) than for insurance against all losses.