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Climate and agricultural risk: measuring the effect of ENSO on U.S. crop insurance

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  • Jesse B. Tack
  • David Ubilava

Abstract

Predictive models of climatic phenomena can aid in insurance program design and decision making. Extreme weather outcomes have been linked to the El Niño Southern Oscillation (ENSO), which globally impacts agricultural production. This study demonstrates that extreme ENSO events alter cotton yield distributions in the Southeastern United States. These impacts translate into economically meaningful effects on crop insurance premium rates. Commercial insurers can use publicly available information to determine if government-set premium rates are mispriced, and in turn extract economic rents via the federally mandated Standard Reinsurance Agreement. By ceding underpriced policies in El Niño and La Niña years, we find that private insurance companies can reduce paid indemnities by 10–15% on average.

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  • Jesse B. Tack & David Ubilava, 2015. "Climate and agricultural risk: measuring the effect of ENSO on U.S. crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 46(2), pages 245-257, March.
    • Handle: RePEc:bla:agecon:v:46:y:2015:i:2:p:245-257
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    2. Gilles Dufrénot & William Ginn & Marc Pourroy, 2023. "ENSO Climate Patterns on Global Economic Conditions," Working Papers hal-04064759, HAL.
    3. Yong Liu & Alan P. Ker, 2021. "Simultaneous borrowing of information across space and time for pricing insurance contracts: An application to rating crop insurance policies," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 231-257, March.
    4. Yaling Li & Fujin Yi & Yanjun Wang & Richard Gudaj, 2019. "The Value of El Niño-Southern Oscillation Forecasts to China’s Agriculture," Sustainability, MDPI, vol. 11(15), pages 1-23, August.
    5. Kulkarni, Kedar, 2021. "Quantifying Vulnerability of Crop Yields in India to Weather Extremes," 2021 Annual Meeting, August 1-3, Austin, Texas 313879, Agricultural and Applied Economics Association.
    6. Andrea Bastianin & Alessandro Lanza & Matteo Manera, 2018. "Economic impacts of El Niño southern oscillation: evidence from the Colombian coffee market," Agricultural Economics, International Association of Agricultural Economists, vol. 49(5), pages 623-633, September.
    7. Hong, Yanran & Yu, Jize & Su, Yuquan & Wang, Lu, 2023. "Southern oscillation: Great value of its trends for forecasting crude oil spot price volatility," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 358-368.
    8. Zhu, Yichen & Ghoshray, Atanu, 2021. "Climate Anomalies and Its Impact on U.S. Corn and Soybean Prices," 2021 Conference, August 17-31, 2021, Virtual 315271, International Association of Agricultural Economists.
    9. Bohorquez-Penuela, Camilo, 2021. "Weather Shocks and Agricultural Credit in Developing Countries: Evidence from a Second-Floor Institution," 2021 Annual Meeting, August 1-3, Austin, Texas 313994, Agricultural and Applied Economics Association.
    10. Checo, Ariadne & Mejía, Mariam & Ramírez, Francisco A., 2017. "El rol de los regímenes de precipitaciones sobre la dinámica de precios y actividad del sector agropecuario de la República Dominicana durante el período 2000-2016 [The role of rainfall regimes on ," MPRA Paper 80301, University Library of Munich, Germany.
    11. Shenan Wu & Barry K. Goodwin & Keith Coble, 2020. "Moral hazard and subsidized crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 51(1), pages 131-142, January.
    12. Fujin Yi & Mengfei Zhou & Yu Yvette Zhang, 2020. "Value of Incorporating ENSO Forecast in Crop Insurance Programs," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 439-457, March.
    13. repec:ags:aaea22:335987 is not listed on IDEAS
    14. A Ford Ramsey, 2020. "Probability Distributions of Crop Yields: A Bayesian Spatial Quantile Regression Approach," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 220-239, January.
    15. Ubilava, David & Orlowski, Jan, 2016. "The Predictive Content of Climate Anomalies for Agricultural Production: Does ENSO Really Matter?," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236281, Agricultural and Applied Economics Association.
    16. Yong Liu & A. Ford Ramsey, 2023. "Incorporating historical weather information in crop insurance rating," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(2), pages 546-575, March.
    17. Jesse Tack & Keith Coble & Barry Barnett, 2018. "Warming temperatures will likely induce higher premium rates and government outlays for the U.S. crop insurance program," Agricultural Economics, International Association of Agricultural Economists, vol. 49(5), pages 635-647, September.
    18. Carter, Colin A. & Schaefer, K. Aleks & Scheitrum, Daniel, 2021. "Raising cane: Hedging calamity in Australian sugar," Journal of Commodity Markets, Elsevier, vol. 21(C).

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