ACTUARIAL IMPLICATIONS OF STRUCTURAL CHANGES IN EL NIÑO-SOUTHERN OSCILLATION INDEX DYNAMICS

The influence of climate variability on agricultural production and financial risks faced by an individual or an institution has been the center of the public discussion in the recent years. The changing weather patterns and environmental conditions could cause substantial unpredicted economic losses. Failure to capture such changes would underestimate the insurance contract's expected indemnity and further create a major obstacle for insurance sectors. In this paper, we undertake a case study of El Niño-Southern Oscillation (ENSO) Index insurance for coastal Peru proposed by Skees. We examined the behavior of El Niño index and uncovered the evidence that the conditional volatility of El Niño index has changed over time. A fractionally integrated GARCH (FIGARCH) process that captures long memory behavior for conditional variance and allows the disturbance variance to vary over time is used to design and rate the ENSO Index insurance contract. Our results show that, with the time-invariant AR(2) model serving as a benchmark, the AR(2)-FIGARCH(1, d, 1) model outperforms the AR(2) model in both in-sample fit and out-of-sample forecast for El Niño index. Moreover, the time-invariant model could underestimate the premium rates, exposing the insurer to undesired underwriting risk and ultimately causing the index insurance market to collapse.