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Copula-Based Models of Systemic Risk in U.S. Agriculture: Implications for Crop Insurance and Reinsurance Contracts

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  • Barry K. Goodwin
  • Ashley Hungerford

Abstract

The federal crop insurance program has been a major fixture of U.S. agricultural policy since the 1930s, and continues to grow in size and importance. Indeed, it now represents the most prominent farm policy instrument, accounting for more government spending than any other farm commodity program. The 2014 Farm Bill further expanded the crop insurance program and introduced a number of new county-level revenue insurance plans. In 2013, over $123 billion in crop value was insured under the program. Crop revenue insurance, first introduced in the 1990s, now accounts for nearly 70% of the total liability in the program. The available plans cover losses that result from a revenue shortfall that can be triggered by multiple, dependent sources of risk-either low prices, low yields, or a combination of both. The actuarial practices currently applied when rating these plans essentially involve the application of a Gaussian copula model to the pricing of dependent risks. We evaluate the suitability of this assumption by considering a number of alternative copula models. In particular, we use combinations of pair-wise copulas of conditional distributions to model multiple sources of risk. We find that this approach is generally preferred by model-fitting criteria in the applications considered here. We demonstrate that alternative approaches to modeling dependencies in a portfolio of risks may have significant implications for premium rates in crop insurance.

Suggested Citation

  • Barry K. Goodwin & Ashley Hungerford, 2015. "Copula-Based Models of Systemic Risk in U.S. Agriculture: Implications for Crop Insurance and Reinsurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(3), pages 879-896.
  • Handle: RePEc:oup:ajagec:v:97:y:2015:i:3:p:879-896.
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    Cited by:

    1. Ceballos, Francisco, 2016. "Estimating spatial basis risk in rainfall index insurance: Methodology and application to excess rainfall insurance in Uruguay," IFPRI discussion papers 1595, International Food Policy Research Institute (IFPRI).
    2. Miao, Ruiqing & Hennessy, David A. & Feng, Hongli, 2016. "The Effects of Crop Insurance Subsidies and Sodsaver on Land-Use Change," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(2), May.
    3. Hongjun Zeng & Ran Lu & Abdullahi D. Ahmed, 2023. "Dynamic dependencies and return connectedness among stock, gold and Bitcoin markets: Evidence from South Asia and China," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 18(1), pages 49-87, March.
    4. Seyyed Ali Zeytoon Nejad Moosavian & Barry K. Goodwin, 2021. "Flexible modelling of multivariate risks in pricing margin protection insurance: modelling portfolio risks with mixtures of mixtures," Applied Economics, Taylor & Francis Journals, vol. 53(4), pages 411-440, January.
    5. Dimitrios Panagiotou & Athanassios Stavrakoudis, 2023. "Price dependence among the major EU extra virgin olive oil markets: a time scale analysis," Review of Agricultural, Food and Environmental Studies, Springer, vol. 104(1), pages 1-26, March.
    6. Negi, Digvijay S., 2018. "Tail-dependent Rainfall Risk and Demand for Index based Crop Insurance," 2018 Annual Meeting, August 5-7, Washington, D.C. 274481, Agricultural and Applied Economics Association.
    7. 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.
    8. Liu, Y. & Ker, A., 2018. "Is There Too Much History in Historical Yield Data," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277293, International Association of Agricultural Economists.
    9. Miao, Ruiqing & Khanna, Madhu, 2017. "Costs of meeting a cellulosic biofuel mandate with perennial energy crops: Implications for policy," Energy Economics, Elsevier, vol. 64(C), pages 321-334.
    10. Awondo, Sebastain N., 2019. "Efficiency of region-wide catastrophic weather risk pools: Implications for African Risk Capacity insurance program," Journal of Development Economics, Elsevier, vol. 136(C), pages 111-118.
    11. A. Ford Ramsey & Sujit K. Ghosh & Barry K. Goodwin, 2020. "Rating exotic price coverage in crop revenue insurance," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 80(5), pages 609-631, May.
    12. Chen, Kuan-Ju & Chen, Kuan-Heng, 2016. "Analysis of Energy and Agricultural Commodity Markets with the Policy Mandated: A Vine Copula-based ARMA-EGARCH Model," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236028, Agricultural and Applied Economics Association.
    13. Panagiotpu, Dimitrios & Stavrakoudis, Athanassios, 2021. "Price dependence among the major EU extra virgin olive oil markets: A time scale analysis," MPRA Paper 114656, University Library of Munich, Germany, revised Jun 2022.
    14. Xiaodong Du & David A Hennessy & Hongli Feng & Gaurav Arora, 2018. "Land Resilience and Tail Dependence among Crop Yield Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(3), pages 809-828.
    15. Lichtenberg, Erik & Iglesias, Eva, 2022. "Index insurance and basis risk: A reconsideration," Journal of Development Economics, Elsevier, vol. 158(C).
    16. Park, Eunchun & Brorsen, Wade & Harri, Ardian, 2017. "Spatially Smoothed Crop Yield Density Estimation: Physical Distance vs Climate Similarity," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259145, Agricultural and Applied Economics Association.
    17. Awondo, Sebastain N. & Shurley, Don W., 2017. "On the Efficiency of Pseudo Risk Pools and Proxy Yield Data on Crop Insurance and Reinsurance in U.S," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258566, Agricultural and Applied Economics Association.
    18. ARAUJO ENCISO Sergio Rene & PIERALLI SIMONE & PEREZ DOMINGUEZ Ignacio, 2017. "Partial Stochastic Analysis with the Aglink-Cosimo Model: A Methodological Overview," JRC Research Reports JRC108837, Joint Research Centre.
    19. Xuche Gong & David A. Hennessy & Hongli Feng, 2023. "Systemic risk, relative subsidy rates, and area yield insurance choice," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(3), pages 888-913, May.
    20. Khaledi-Alamdari, Mohammad & Majnooni-Heris, Abolfazl & Fakheri-Fard, Ahmad & Russo, Ana, 2023. "Probabilistic climate risk assessment in rainfed wheat yield: Copula approach using water requirement satisfaction index," Agricultural Water Management, Elsevier, vol. 289(C).
    21. Belasco, Eric J., 2020. "WAEA Presidential Address: Moving Agricultural Policy Forward: Or, There and Back Again," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 45(3), September.
    22. Bousebata, Meryem & Enjolras, Geoffroy & Girard, Stéphane, 2020. "The dependence structure between yields and prices: A copula-based model of French farm income," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304313, Agricultural and Applied Economics Association.

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