IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i9p7133-d1131752.html
   My bibliography  Save this article

Remote Sensing Application in Pure Premium Rate-Making of Winter Wheat Crop Insurance

Author

Listed:
  • Weijia Wang

    (Center for Spatial Information, School of Environment and Natural Resources, Renmin University of China, Beijing 100872, China)

  • Wen Wang

    (Center for Spatial Information, School of Environment and Natural Resources, Renmin University of China, Beijing 100872, China)

  • Kun Wang

    (Center for Spatial Information, School of Environment and Natural Resources, Renmin University of China, Beijing 100872, China)

  • Yanyun Zhao

    (School of Statistics, Renmin University of China, Beijing 100872, China)

  • Ran Yu

    (Center for Spatial Information, School of Environment and Natural Resources, Renmin University of China, Beijing 100872, China)

Abstract

Crop insurance is a crucial way to avoid disaster losses and to guarantee farmers’ basic production income in China and abroad. Securing agricultural production is a critical way to eradicate hunger and reduce poverty and an essential means to achieve the UN Sustainable Development Goals. How to pay out more quickly and fairly after a disaster has become an urgent issue for agricultural insurance. The standard domestic crop insurance rate is determined based on the statistical data of the entire administrative unit and ignores the spatial risk difference of disasters inside the administrative unit. Therefore, obtaining a pure premium based on crops inside the administrative unit is a key problem. Based on remote sensing data and insurance actuarial models, we studied and determined the fair premium rates to insure winter wheat at the farmer level in Heze, Shandong, China. Our study shows that remote sensing data can provide data security for determining a pure premium rate at the level of individual farms, and provide the primary reference for determining farmer-level crop insurance premium rates. The use of remote sensing for determining those rates can improve the customization of crop insurance and reduce farmers’ lower incomes due to exposure to natural disasters, improve farmers’ resilience to risk, and prevent a return to poverty due to disasters, ultimately reaching the UN Sustainable Development goals of eradicating hunger and reducing poverty.

Suggested Citation

  • Weijia Wang & Wen Wang & Kun Wang & Yanyun Zhao & Ran Yu, 2023. "Remote Sensing Application in Pure Premium Rate-Making of Winter Wheat Crop Insurance," Sustainability, MDPI, vol. 15(9), pages 1-15, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7133-:d:1131752
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/9/7133/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/9/7133/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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, vol. 12(6), pages 1-15, March.
    2. Jerry R. Skees & J. Roy Black & Barry J. Barnett, 1997. "Designing and Rating an Area Yield Crop Insurance Contract," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(2), pages 430-438.
    3. Xiaodong Du & Hongli Feng & David A. Hennessy, 2017. "Rationality of Choices in Subsidized Crop Insurance Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 732-756.
    4. Go Shimada, 2022. "The Impact of Climate-Change-Related Disasters on Africa’s Economic Growth, Agriculture, and Conflicts: Can Humanitarian Aid and Food Assistance Offset the Damage?," IJERPH, MDPI, vol. 19(1), pages 1-16, January.
    5. Yuqiang Gao & Yongkang Shu & Hongjie Cao & Shuting Zhou & Shaobin Shi, 2021. "Fiscal Policy Dilemma in Resolving Agricultural Risks: Evidence from China’s Agricultural Insurance Subsidy Pilot," IJERPH, MDPI, vol. 18(14), pages 1-11, July.
    6. Min Zhou & Hua Zhang & Nan Ke, 2022. "Cultivated Land Transfer, Management Scale, and Cultivated Land Green Utilization Efficiency in China: Based on Intermediary and Threshold Models," IJERPH, MDPI, vol. 19(19), pages 1-20, October.
    7. Chao Hu & Damian C. Adams & Huachao Feng & Jing Cheng, 2023. "Refining the Rent Dissipation Model in Land Use: Application to Agricultural Insurance in China," Land, MDPI, vol. 12(2), pages 1-18, January.
    8. Jason Hickel, 2019. "The contradiction of the sustainable development goals: Growth versus ecology on a finite planet," Sustainable Development, John Wiley & Sons, Ltd., vol. 27(5), pages 873-884, September.
    9. Mario J. Miranda, 1991. "Area-Yield Crop Insurance Reconsidered," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 73(2), pages 233-242.
    10. Xiaodong Du & Hongli Feng & David A. Hennessy, 2017. "Rationality of Choices in Subsidized Crop Insurance Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 732-756.
    11. Barry K. Goodwin & Alan P. Ker, 1998. "Nonparametric Estimation of Crop Yield Distributions: Implications for Rating Group-Risk Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 139-153.
    12. Shweta Sinha & Nitin K. Tripathi, 2016. "Assessing the Challenges in Successful Implementation and Adoption of Crop Insurance in Thailand," Sustainability, MDPI, vol. 8(12), pages 1-20, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Douadia Bougherara & Laurent Piet, 2018. "On the role of probability weighting on WTP for crop insurance with and without yield skewness," Working Papers hal-02790605, HAL.
    2. Paulson, Nicholas D. & Babcock, Bruce A., 2008. "Get a Grip: Should Area Revenue Coverage Be Offered Through the Farm Bill or as a Crop Insurance Program?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 33(2), pages 1-17.
    3. Park, Eunchun & Brorsen, B. Wade & Harri, Ardian, 2016. "Using Bayesian Spatial Smoothing and Extreme Value Theory to Develop Area-Yield Crop Insurance Rating," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235754, Agricultural and Applied Economics Association.
    4. Coble, Keith H. & Barnett, Barry J., 1999. "The Role Of Research In Producer Risk Management," Professional Papers 15803, Mississippi State University, Department of Agricultural Economics.
    5. Ramirez, Octavio A. & Shonkwiler, J. Scott, 2017. "A Probabilistic Model of Crop Insurance Purchase Decision," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 42(1), pages 1-17, January.
    6. Ramsey, Ford, 2014. "An Application of Kernel Density Estimation via Diffusion to Group Yield Insurance," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170173, Agricultural and Applied Economics Association.
    7. Ramirez, Octavio & Shonkwiler, J. Scott, 2016. "Some Comparative Statics for Evaluating the Performance of the US Crop Insurance Program," SCC-76 Meeting, 2016, March 17-19, Pensacola, Florida 233761, SCC-76: Economics and Management of Risk in Agriculture and Natural Resources.
    8. Matthew Stuart & Cindy Yu & David A. Hennessy, 2023. "The Impact of Stocks on Correlations between Crop Yields and Prices and on Revenue Insurance Premiums using Semiparametric Quantile Regression," Papers 2308.11805, arXiv.org, revised Jun 2024.
    9. Chen, Shu-Ling & Miranda, Mario J., 2006. "Modeling Yield Distribution In High Risk Counties: Application To Texas Upland Cotton," 2006 Annual meeting, July 23-26, Long Beach, CA 21392, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Adhikari, Shyam & Knight, Thomas O. & Belasco, Eric J., 2012. "Evaluation of Crop Insurance Yield Guarantees and Producer Welfare with Upward-Trending Yields," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 41(3), pages 1-10, December.
    11. Glauber, Joseph W., 2017. "Agricultural insurance and the WTO:," IFPRI book chapters, in: Bouët, Antoine & Laborde Debucquet, David (ed.), Agriculture, development, and the global trading system: 2000– 2015, chapter 10, International Food Policy Research Institute (IFPRI).
    12. Bougherara, Douadia & Piet, Laurent, 2014. "The Impact of Farmers’ Risk Preferences on the Design of an Individual Yield Crop Insurance," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 183082, European Association of Agricultural Economists.
    13. Shih-Chieh Liao & Shih-Chieh Chang & Tsung-Chi Cheng, 2021. "Managing the Volatility Risk of Renewable Energy: Index Insurance for Offshore Wind Farms in Taiwan," Sustainability, MDPI, vol. 13(16), pages 1-27, August.
    14. Bokusheva, Raushan, 2010. "Measuring the dependence structure between yield and weather variables," MPRA Paper 22786, University Library of Munich, Germany.
    15. Mahul, Olivier, 2002. "Hedging Price Risk in the Presence of Crop Yield and Revenue Insurance," 2002 International Congress, August 28-31, 2002, Zaragoza, Spain 24881, European Association of Agricultural Economists.
    16. Hanson, Steven D. & Black, J. Roy & Wang, H. Holly, 2000. "Can Revenue Insurance Substitute For Price And Yield Risk Management Instruments?," Staff Paper Series 11655, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    17. Hennessy, David A., 1998. "Risk Market Innovations and Choice," International Review of Economics & Finance, Elsevier, vol. 7(3), pages 331-341.
    18. repec:ags:ijag24:345239 is not listed on IDEAS
    19. Mahul, Olivier & Vermersch, Dominique, 1999. "Hedging Crop Risk With Yield Insurance Futures And Options," 1999 Annual meeting, August 8-11, Nashville, TN 21672, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    20. Clop-Gallart, M. Merce & Juarez-Rubio, Francisco, 2008. "Shape Persistence in Elicited Subjective Crop Yield Probability Density Functions," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44128, European Association of Agricultural Economists.
    21. Mitchell, Paul D. & Knight, Thomas O., 2008. "Economic Analysis of Supplemental Deductible Coverage as Recommended in the USDA's 2007 Farm Bill Proposal," Agricultural and Resource Economics Review, Cambridge University Press, vol. 37(1), pages 117-131, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7133-:d:1131752. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.