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Systemic Weather Risk and Crop Insurance: The Case of China

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  • Wei Xu
  • Ostap Okhrin
  • Martin Odening
  • Ji Cao

Abstract

The supply of affordable crop insurance is hampered by the existence of systemic weather risk which results in large risk premiums. In this article, we assess the systemic nature of weather risk for 17 agricultural production regions in China and explore the possibility of spatial diversification of this risk. We simulate the buffer load of hypothetical temperature-based insurance and investigate the relation between the size of the buffer load and the size of the trading area of the insurance. The analysis makes use of a hierarchical Archimedean copula approach (HAC) which allows flexible modeling of the joint loss distribution and reveals the dependence structure of losses in different insured regions. Our results show a significant decrease of the required risk loading when the insured area expands. Nevertheless, a considerable part of undiversifiable risk remains with the insurer. We find that the spatial diversification effect depends on the type of the weather index and the strike level of the insurance. Our findings are relevant for insurers and insurance regulators as they shed light on the viability of private crop insurance in China.

Suggested Citation

  • Wei Xu & Ostap Okhrin & Martin Odening & Ji Cao, 2010. "Systemic Weather Risk and Crop Insurance: The Case of China," SFB 649 Discussion Papers SFB649DP2010-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Handle: RePEc:hum:wpaper:sfb649dp2010-053
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    References listed on IDEAS

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    Cited by:

    1. Nicole Wiebach & Lutz Hildebrandt, 2010. "Context Effects as Customer Reaction on Delisting of Brands," SFB 649 Discussion Papers SFB649DP2010-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. 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).
    3. Lysa Porth & Milton Boyd & Jeffrey Pai, 2016. "Reducing Risk Through Pooling and Selective Reinsurance Using Simulated Annealing: An Example from Crop Insurance," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 41(2), pages 163-191, September.
    4. Christian Biener & Martin Eling & Shailee Pradhan, 2015. "Recent Research Developments Affecting Nonlife Insurance—The CAS Risk Premium Project 2013 Update," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 18(1), pages 129-141, March.
    5. Basteck, Christian & Daniëls, Tijmen R., 2011. "Every symmetric 3×3 global game of strategic complementarities has noise-independent selection," Journal of Mathematical Economics, Elsevier, vol. 47(6), pages 749-754.
    6. Sheng, Di & Lambert, Dayton M. & Hellwinckel, Chad, 2016. "A Copula-based Approach to Simulate Climate Impacts on Yield: Some Preliminary Findings," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230006, Southern Agricultural Economics Association.
    7. Ostap Okhrin & Alexander Ristig & Jeffrey Sheen & Stefan Trück, 2015. "Conditional Systemic Risk with Penalized Copula," SFB 649 Discussion Papers SFB649DP2015-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Zhiwei Shen & Martin Odening & Ostap Okhrin, 2016. "Can expert knowledge compensate for data scarcity in crop insurance pricing?," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 43(2), pages 237-269.
    9. Enno Mammen & Christoph Rothe & Melanie Schienle, 2010. "Nonparametric Regression with Nonparametrically Generated Covariates," SFB 649 Discussion Papers SFB649DP2010-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    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. Ben Ammar, Semir & Braun, Alexander & Eling, Martin, 2015. "Alternative Risk Transfer and Insurance-Linked Securities: Trends, Challenges and New Market Opportunities," I.VW HSG Schriftenreihe, University of St.Gallen, Institute of Insurance Economics (I.VW-HSG), volume 56, number 56, December.
    12. Lysa Porth & Milton Boyd & Jeffrey Pai, 2016. "Reducing Risk Through Pooling and Selective Reinsurance Using Simulated Annealing: An Example from Crop Insurance," The Geneva Papers on Risk and Insurance Theory, Springer;International Association for the Study of Insurance Economics (The Geneva Association), vol. 41(2), pages 163-191, September.
    13. Lu Zong & Manuela Ender, 2016. "Spatially-Aggregated Temperature Derivatives: Agricultural Risk Management in China," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 4(3), pages 1-17, September.
    14. Wu, Yang-Che, 2020. "Equilibrium in natural catastrophe insurance market under disaster-resistant technologies, financial innovations and government interventions," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 116-128.
    15. Zhiwei Shen & Martin Odening, 2013. "Coping with systemic risk in index-based crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 44(1), pages 1-13, January.
    16. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2014. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 12(1), pages 89-121.
    17. Franziska Schulze, 2010. "Spatial Dependencies in German Matching Functions," SFB 649 Discussion Papers SFB649DP2010-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Gong, Xuche & Feng, Hongli & Hennessy, David A., 2018. "Systemic Risk, Geography and Area Insurance," 2018 Annual Meeting, August 5-7, Washington, D.C. 274479, Agricultural and Applied Economics Association.
    19. Ying-Erh Chen & Barry K Goodwin, 2015. "Policy Design of Multi-Year Crop Insurance Contracts with Partial Payments," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-15, December.
    20. Xiaofeng Cao & Ostap Okhrin & Martin Odening & Matthias Ritter, 2015. "Modelling spatio-temporal variability of temperature," Computational Statistics, Springer, vol. 30(3), pages 745-766, September.
    21. Zhu, Wenjun & Wang, Chou-Wen & Tan, Ken Seng, 2016. "Structure and estimation of Lévy subordinated hierarchical Archimedean copulas (LSHAC): Theory and empirical tests," Journal of Banking & Finance, Elsevier, vol. 69(C), pages 20-36.
    22. Feng, Xiaoguang & Hayes, Dermot, 2014. "Is Government Involvement Really Necessary: Implications for Systemic Risk and Crop Reinsurance Contracts," 2014 AAEA: Crop Insurance and the 2014 Farm Bill Symposium: Implementing Change in U.S. Agricultural Policy, October 8-9, 2014, Louisville, KY 184241, Agricultural and Applied Economics Association.
    23. Franziska Gaupp & Georg Pflug & Stefan Hochrainer‐Stigler & Jim Hall & Simon Dadson, 2017. "Dependency of Crop Production between Global Breadbaskets: A Copula Approach for the Assessment of Global and Regional Risk Pools," Risk Analysis, John Wiley & Sons, vol. 37(11), pages 2212-2228, November.
    24. Xiaotao Li & Jinzheng Ren & Beibei Niu & Haiping Wu, 2020. "Grain Area Yield Index Insurance Ratemaking Based on Time–Space Risk Adjustment in China," Sustainability, MDPI, Open Access Journal, vol. 12(6), pages 1-15, March.
    25. Yuehua Zhang & Ying Cao & H. Holly Wang, 2018. "Cheating? The Case of Producers’ Under‐Reporting Behavior in Hog Insurance in China," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 66(3), pages 489-510, September.

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    More about this item

    Keywords

    crop insurance; systemic weather risk; hierarchical Archimedean copulas;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • Q19 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Other

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