IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v15y2025i14p1473-d1698225.html

Enhancing Farmer Resilience Through Agricultural Insurance: Evidence from Jiangsu, China

Author

Listed:
  • Xinru Chen

    (Faculty of Finance and Economics, Jiangsu University, No. 301 Xue Fu Road, Zhenjiang 212013, China)

  • Yuan Jiang

    (Faculty of Finance and Economics, Jiangsu University, No. 301 Xue Fu Road, Zhenjiang 212013, China)

  • Tianwei Wang

    (School of Mathematical Sciences, Jiangsu University, No. 301 Xue Fu Road, Zhenjiang, 212013, China)

  • Kexuan Zhou

    (School of Mathematical Sciences, Jiangsu University, No. 301 Xue Fu Road, Zhenjiang, 212013, China)

  • Jiayi Liu

    (Faculty of Finance and Economics, Jiangsu University, No. 301 Xue Fu Road, Zhenjiang 212013, China)

  • Huirong Ben

    (Faculty of Finance and Economics, Jiangsu University, No. 301 Xue Fu Road, Zhenjiang 212013, China)

  • Weidong Wang

    (Faculty of Finance and Economics, Jiangsu University, No. 301 Xue Fu Road, Zhenjiang 212013, China)

Abstract

Against the backdrop of evolving global climate patterns, the frequency and intensity of extreme weather events have increased significantly, posing unprecedented threats to agricultural production. This change has particularly profound impacts on agricultural systems in developing countries, making the enhancement of farmers’ capacity to withstand extreme weather events a crucial component for achieving sustainable agricultural development. As an essential safeguard for agricultural production, agricultural insurance plays an indispensable role in risk management. However, a pronounced gap persists between policy aspirations and actual adoption rates among farmers in developing economies. This study employs the integrated theory of planned behavior (TPB) and protection motivation theory (PMT) to construct an analytical framework incorporating psychological, socio-cultural, and risk-perception factors. Using Jiangsu Province—a representative high-risk agricultural region in China—as a case study, we administered 608 structured questionnaires to farmers. Structural equation modeling was applied to identify determinants influencing insurance adoption decisions. The findings reveal that farmers’ agricultural insurance purchase decisions are influenced by multiple factors. At the individual level, risk perception promotes purchase intention by activating protection motivation, while cost–benefit assessment enables farmers to make rational evaluations. At the social level, subjective norms can significantly enhance farmers’ purchase intention. Further analysis indicates that perceived severity indirectly enhances purchase intention by positively influencing attitude, while response costs negatively affect purchase intention by weakening perceived behavior control. Although challenges such as cognitive gaps and product mismatch exist in the intention-behavior transition, institutional trust can effectively mitigate these issues. It not only strengthens the positive impact of psychological factors on purchase intention, but also significantly facilitates the transformation of purchase intention into actual behavior. To promote targeted policy interventions for agricultural insurance, we propose corresponding policy recommendations from the perspective of public intervention based on the research findings.

Suggested Citation

  • Xinru Chen & Yuan Jiang & Tianwei Wang & Kexuan Zhou & Jiayi Liu & Huirong Ben & Weidong Wang, 2025. "Enhancing Farmer Resilience Through Agricultural Insurance: Evidence from Jiangsu, China," Agriculture, MDPI, vol. 15(14), pages 1-30, July.
  • Handle: RePEc:gam:jagris:v:15:y:2025:i:14:p:1473-:d:1698225
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/15/14/1473/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/15/14/1473/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carter, Michael R. & Cheng, Lan & Sarris, Alexandros, 2016. "Where and how index insurance can boost the adoption of improved agricultural technologies," Journal of Development Economics, Elsevier, vol. 118(C), pages 59-71.
    2. Fahad, Shah & Wang, Jing & Hu, Guangyin & Wang, Hui & Yang, Xiaoying & Shah, Ashfaq Ahmad & Huong, Nguyen Thi Lan & Bilal, Arshad, 2018. "Empirical analysis of factors influencing farmers crop insurance decisions in Pakistan: Evidence from Khyber Pakhtunkhwa province," Land Use Policy, Elsevier, vol. 75(C), pages 459-467.
    3. Hans P. Binswanger-Mkhize, 2012. "Is There Too Much Hype about Index-based Agricultural Insurance?," Journal of Development Studies, Taylor & Francis Journals, vol. 48(2), pages 187-200, February.
    4. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    5. Bruce J. Sherrick & Peter J. Barry & Paul N. Ellinger & Gary D. Schnitkey, 2004. "Factors Influencing Farmers' Crop Insurance Decisions," American Journal of Agricultural Economics, John Wiley & Sons, vol. 86(1), pages 103-114, February.
    6. Codruţa Mare & Daniela Manaţe & Gabriela-Mihaela Mureşan & Simona Laura Dragoş & Cristian Mihai Dragoş & Alexandra-Anca Purcel, 2022. "Machine Learning Models for Predicting Romanian Farmers’ Purchase of Crop Insurance," Mathematics, MDPI, vol. 10(19), pages 1-13, October.
    7. Katrina Jessoe & David Rapson, 2014. "Knowledge Is (Less) Power: Experimental Evidence from Residential Energy Use," American Economic Review, American Economic Association, vol. 104(4), pages 1417-1438, April.
    8. Guoyong Wu & Jianwei Cheng & Fan Yang, 2022. "The Influence of the Peer Effect on Farmers’ Agricultural Insurance Decision: Evidence from the Survey Data of the Karst Region in China," Sustainability, MDPI, vol. 14(19), pages 1-14, September.
    9. Joseph W. Glauber, 2004. "Crop Insurance Reconsidered," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(5), pages 1179-1195.
    10. Birthal, Pratap S. & Hazrana, Jaweriah & Negi, Digvijay S. & Mishra, Ashok K., 2022. "Assessing benefits of crop insurance vis-a-vis irrigation in Indian agriculture," Food Policy, Elsevier, vol. 112(C).
    11. Dean Karlan & Robert Osei & Isaac Osei-Akoto & Christopher Udry, 2014. "Agricultural Decisions after Relaxing Credit and Risk Constraints," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(2), pages 597-652.
    12. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    13. Wenjian He & Yiyang Liu & Huaping Sun & Farhad Taghizadeh-Hesary, 2020. "How Does Climate Change Affect Rice Yield in China?," Agriculture, MDPI, vol. 10(10), pages 1-16, September.
    14. Xueling Bao & Fengwan Zhang & Shili Guo & Xin Deng & Jiahao Song & Dingde Xu, 2022. "Peer Effects on Farmers’ Purchases of Policy-Based Planting Farming Agricultural Insurance: Evidence from Sichuan Province, China," IJERPH, MDPI, vol. 19(12), pages 1-18, June.
    15. Geoffroy Enjolras & Patrick Sentis, 2011. "Crop insurance policies and purchases in France," Agricultural Economics, International Association of Agricultural Economists, vol. 42(4), pages 475-486, July.
    16. Ruikun Peng & Yinyin Zhao & Ehsan Elahi & Benhong Peng, 2021. "Does disaster shocks affect farmers’ willingness for insurance? Mediating effect of risk perception and survey data from risk-prone areas in East China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(3), pages 2883-2899, April.
    17. Daniel R. Petrolia & Craig E. Landry & Keith H. Coble, 2013. "Risk Preferences, Risk Perceptions, and Flood Insurance," Land Economics, University of Wisconsin Press, vol. 89(2), pages 227-245.
    18. 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.
    19. Mustapha Yakubu Madaki & Harald Kaechele & Miroslava Bavorova, 2023. "Agricultural insurance as a climate risk adaptation strategy in developing countries: a case of Nigeria," Climate Policy, Taylor & Francis Journals, vol. 23(6), pages 747-762, July.
    20. Wong, Ho Lun & Wei, Xiangdong & Kahsay, Haftom Bayray & Gebreegziabher, Zenebe & Gardebroek, Cornelis & Osgood, Daniel E. & Diro, Rahel, 2020. "Effects of input vouchers and rainfall insurance on agricultural production and household welfare: Experimental evidence from northern Ethiopia," World Development, Elsevier, vol. 135(C).
    21. Amare Wodaju & Zerihun Nigussie & Asresu Yitayew & Bosena Tegegne & Atalel Wubalem & Steffen Abele, 2025. "Factors influencing farmers’ willingness to pay for weather-indexed crop insurance policies in rural Ethiopia," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(4), pages 8951-8976, April.
    22. Dragos, Cristian Mihai & Dragos, Simona Laura & Mare, Codruta & Muresan, Gabriela Mihaela & Purcel, Alexandra-Anca, 2023. "Does risk assessment and specific knowledge impact crop insurance underwriting? Evidence from Romanian farmers," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 343-358.
    23. Robert G. Chambers, 1989. "Insurability and Moral Hazard in Agricultural Insurance Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(3), pages 604-616.
    24. Bruce J. Sherrick & Peter J. Barry & Paul N. Ellinger & Gary D. Schnitkey, 2004. "Factors Influencing Farmers' Crop Insurance Decisions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(1), pages 103-114.
    25. Bungchay Lay & Isriya Bunyasiri & Ravissa Suchato, 2023. "Farmers’ Willingness to Purchase Weather Index Crop Insurance: Evidence from Battambang, Cambodia," JRFM, MDPI, vol. 16(12), pages 1-9, November.
    26. Ashok Mishra & Barry Goodwin, 2006. "Revenue insurance purchase decisions of farmers," Applied Economics, Taylor & Francis Journals, vol. 38(2), pages 149-159.
    27. Noelwah R. Netusil & Carolyn Kousky & Shulav Neupane & Will Daniel & Howard Kunreuther, 2021. "The Willingness to Pay for Flood Insurance," Land Economics, University of Wisconsin Press, vol. 97(1), pages 17-38.
    28. Xinya Guo & Yuanfeng Zhao & Muhammad Umer Arshad & Yufei Gong & Polinpapilinho Katina, 2022. "Farmers’ Willingness to Pay a High Premium for Different Types of Agricultural Insurance: Evidence from Inner Mongolia, China," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-9, March.
    29. Platteau, Jean-Philippe & Ugarte Ontiveros, Darwin, 2021. "Cognitive bias in insurance: Evidence from a health scheme in India," World Development, Elsevier, vol. 144(C).
    30. Sampath Sanjeewa Weedige & Hongbing Ouyang & Yao Gao & Yaqing Liu, 2019. "Decision Making in Personal Insurance: Impact of Insurance Literacy," Sustainability, MDPI, vol. 11(23), pages 1-24, November.
    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. Vigani, Mauro & Khafagy, Amr & Berry, Robert, 2024. "Public spending for agricultural risk management: Land use, regional welfare and intra-subsidy substitution," Food Policy, Elsevier, vol. 123(C).
    2. Richard KOENIG & Marielle BRUNETTE, 2023. "Subjective barriers and determinants to crop insurance adoption," Working Papers of BETA 2023-25, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    3. Tao Ye & Yangbin Liu & Jiwei Wang & Ming Wang & Peijun Shi, 2017. "Farmers’ crop insurance perception and participation decisions: empirical evidence from Hunan, China," Journal of Risk Research, Taylor & Francis Journals, vol. 20(5), pages 664-677, May.
    4. Belissa, Temesgen K. & Lensink, Robert & Marr, Ana, 2025. "The impact of bundling index insurance with credit and input vouchers: Experimental evidence from Ethiopia," Journal of Economic Behavior & Organization, Elsevier, vol. 234(C).
    5. Giampietri, Elisa & Yu, Xiaohua & Trestini, Samuele, . "The role of trust and perceived barriers on farmer’s intention to adopt risk management tools," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 9(01).
    6. Jialin Wang & Yanglin Wu & Jiyao Liu & Desheng Zhang, 2025. "Study of the Impact of Agricultural Insurance on the Livelihood Resilience of Farmers: A Case Study of Comprehensive Natural Rubber Insurance," Agriculture, MDPI, vol. 15(15), pages 1-23, August.
    7. Ward, Patrick S. & Kumar, Neha & De Nicola, Francesca & Hill, Ruth & Makhija, Simrin & Spielman, David J. & Magnan, Nicholas, "undated". "Insuring Against Drought: Evidence on Agricultural Intensification and Demand for Index Insurance from a Randomized Evaluation in Rural Bangladesh," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258090, Agricultural and Applied Economics Association.
    8. Leblois, A. & Le Cotty, T. & Maître d'Hôtel, E., 2020. "How Might Climate Change Influence farmers' Demand for Index-Based Insurance?," Ecological Economics, Elsevier, vol. 176(C).
    9. Hill, Ruth Vargas & Kumar, Neha & Magnan, Nicholas & Makhija, Simrin & de Nicola, Francesca & Spielman, David J. & Ward, Patrick S., 2019. "Ex ante and ex post effects of hybrid index insurance in Bangladesh," Journal of Development Economics, Elsevier, vol. 136(C), pages 1-17.
    10. Chemeris, Anna & Liu, Yong & Ker, Alan P., 2022. "Insurance subsidies, climate change, and innovation: Implications for crop yield resiliency," Food Policy, Elsevier, vol. 108(C).
    11. Ming Wang & Tao Ye & Peijun Shi, 2016. "Factors Affecting Farmers’ Crop Insurance Participation in China," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(3), pages 479-492, September.
    12. Shin, Soye & Magnan, Nicholas & Mullally, Conner & Janzen, Sarah, 2022. "Demand for Weather Index Insurance among Smallholder Farmers under Prospect Theory," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 82-104.
    13. Kenneth W. Sibiko & Matin Qaim, 2020. "Weather index insurance, agricultural input use, and crop productivity in Kenya," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 12(1), pages 151-167, February.
    14. Nathaniel Jensen & Christopher Barrett, 2017. "Agricultural Index Insurance for Development," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 39(2), pages 199-219.
    15. Birthal, Pratap S. & Hazrana, Jaweriah & Negi, Digvijay S. & Mishra, Ashok K., 2022. "Assessing benefits of crop insurance vis-a-vis irrigation in Indian agriculture," Food Policy, Elsevier, vol. 112(C).
    16. Hill, Ruth Vargas & Kumar, Neha & Magnan, Nicholas & Makhija, Simrin & de Nicola, Francesca & Spielman, David J. & Ward, Patrick S., 2017. "Insuring against droughts: Evidence on agricultural intensification and index insurance demand from a randomized evaluation in rural Bangladesh," IFPRI discussion papers 1630, International Food Policy Research Institute (IFPRI).
    17. Mbonane, Nobuhle Duduzile, 2018. "An analysis of farmers’ preferences for crop insurance: a case of maize farmers in Swaziland," Research Theses 334771, Collaborative Masters Program in Agricultural and Applied Economics.
    18. Codruţa Mare & Daniela Manaţe & Gabriela-Mihaela Mureşan & Simona Laura Dragoş & Cristian Mihai Dragoş & Alexandra-Anca Purcel, 2022. "Machine Learning Models for Predicting Romanian Farmers’ Purchase of Crop Insurance," Mathematics, MDPI, vol. 10(19), pages 1-13, October.
    19. Heidelbach, Olaf, 2007. "Efficiency of selected risk management instruments: An empirical analysis of risk reduction in Kazakhstani crop production," Studies on the Agricultural and Food Sector in Transition Economies, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), volume 40, number 92323.
    20. Hui Mao & Shaojian Chen & RuiYao Ying & Yong Fu, 2023. "How crop insurance influences agrochemical input use: Evidence from cotton farmers in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(2), pages 224-244, April.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jagris:v:15:y:2025:i:14:p:1473-:d:1698225. 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.