Value of Incorporating ENSO Forecast in Crop Insurance Programs

Abstract

Agricultural production is substantially affected by the variations in global weather patterns, particularly by the El Niño–Southern Oscillation (ENSO). Thus, incorporating the forecast of imminent ENSO phases can enhance the effectiveness of crop insurance and mitigate the adverse impacts of weather on agriculture. Given the probabilistic nature of the ENSO phase forecast, we employ a Bayesian framework to estimate the value of ENSO information on various aspects of crop insurance. Our results indicate potential benefits of ENSO forecast to insurance rate setting and policy selection. At the same time, we caution against overoptimism in this assessment as economic benefits may diminish as the accuracy of ENSO forecast decreases. Simulations and numerical experiments demonstrate the practical usefulness of the proposed method for various stakeholders of the US crop insurance industry. Implications to various crop insurance policies are also discussed.

Towards a Sustainable Agricultural Credit Guarantee Scheme

“…There are already some developments on the use of seasonal forecasts. For instance, Yi et al (2020) discuss the use of ENSO forecasts for rate making. Further work should consider the use of country or region-specific Seasonal Climate Forecasts by different stakeholders, including farmers and Governments.…”

Incorporating historical weather information in crop insurance rating

“…Nadolnyak et al (2008) studied the value of including information on the El Niño Southern Oscillation (ENSO) in constructing climate-based yield forecasts. The effects of ENSO were further investigated by Tack and Ubilava (2015) and Yi et al (2020). Of these, only Yi et al (2020) incorporates the uncertain nature of ENSO forecasts; this is done in a quasi-Bayesian framework.…”

“…The effects of ENSO were further investigated by Tack and Ubilava (2015) and Yi et al (2020). Of these, only Yi et al (2020) incorporates the uncertain nature of ENSO forecasts; this is done in a quasi‐Bayesian framework. Outside of multiple‐peril crop insurance, weather and other risk management instruments have been discussed by Turvey (2001), Xu et al (2010), and Dalhaus et al (2020).…”

“…Weather information is also frequently used by reinsurers when evaluating crop insurance portfolios and portfolio risk (Zhu et al 2019). Weather‐conditioned distributions have been shown to roughly approximate yield distributions based on observed yields and several studies have discussed the potential benefits of using weather or climate information in crop insurance rating (Goodwin 2008; Nadolnyak et al 2008; Tack & Ubilava 2015; Tack et al 2018; Yi et al 2020).…”

Heterogeneous impacts of the spot check‐list program in US crop insurance: A disaggregated analysis at the crop level

“…As a result, higher‐risk farmers are more likely to purchase crop insurance, resulting in larger than expected indemnity payments. Many studies in the literature have examined how the actuarial performance of FCIP can be improved through better rate‐making procedures to address adverse selection (e.g., Knight et al, 2010; Liu & Ramesey, 2022; Tack & Ubilava, 2015; Tsiboe & Tack, 2022; Yi et al, 2020).…”