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Do forest producers benefit from the forest disaster insurance program? Empirical evidence in Fujian Province of China

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  • Dai, Yongwu
  • Chang, Hung-Hao
  • Liu, Weiping

Abstract

Disaster insurance programs have been recognized as an effective strategy to reduce agricultural production risk. Although a considerable body of literature has focused on natural disaster insurance programs for agricultural producers, not much is known about forest disaster insurance. This paper contributes to this knowledge gap by looking at the Fujian Forest Disaster Insurance (FFDI) program in China. In particular, we examine the extent to which the socio-demographic characteristics and production practice of forest producers, along with other factors, are associated with their participation decision to the program. Moreover, we assess the impact of the FFDI program on household income. Using a household survey of 950 forest producers in Fujian Province in China, it is evident that the education of forest producers, participation in producers' organizations in the local area, and the incidence of forest fires in the local counties are significant determinants of participation in the FFDI program. With respect to the welfare effect, we found that the FFDI program significantly increased household income by approximately 10%.

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  • Dai, Yongwu & Chang, Hung-Hao & Liu, Weiping, 2015. "Do forest producers benefit from the forest disaster insurance program? Empirical evidence in Fujian Province of China," Forest Policy and Economics, Elsevier, vol. 50(C), pages 127-133.
  • Handle: RePEc:eee:forpol:v:50:y:2015:i:c:p:127-133
    DOI: 10.1016/j.forpol.2014.06.001
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    Cited by:

    1. Feng, Xin & Dai, Yongwu, 2019. "An innovative type of forest insurance in China based on the robust approach," Forest Policy and Economics, Elsevier, vol. 104(C), pages 23-32.
    2. Ning, Manxiu & Gong, Jinquan & Zheng, Xuhui & Zhuang, Jun, 2016. "Does New Rural Pension Scheme decrease elderly labor supply? Evidence from CHARLS," China Economic Review, Elsevier, vol. 41(C), pages 315-330.
    3. Yiling Deng & Ian A. Munn & Haibo Yao, 2021. "Attributes‐based conjoint analysis of landowner preferences for standing timber insurance," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 24(4), pages 421-444, December.
    4. Marielle Brunette & Stéphane Couture & Jérôme Foncel & Serge S. Garcia, 2017. "Insurance decision against forest fire : An econometric analysis combining experimental and real data," Post-Print hal-02785187, HAL.
    5. Yang Cai & Lianshui Li & Ehsan Elahi & Yueming Qiu, 2018. "Selection of Policies on Typhoon and Rainstorm Disasters in China: A Content Analysis Perspective," Sustainability, MDPI, vol. 10(2), pages 1-13, February.
    6. Bastit, Félix & Brunette, Marielle & Montagné-Huck, Claire, 2023. "Pests, wind and fire: A multi-hazard risk review for natural disturbances in forests," Ecological Economics, Elsevier, vol. 205(C).
    7. Junying Lin & Zhonggen Zhang & Lingli Lv, 2019. "The Impact of Program Participation on Rural Household Income: Evidence from China’s Whole Village Poverty Alleviation Program," Sustainability, MDPI, vol. 11(6), pages 1-15, March.
    8. Sandrine Brèteau-Amores & Marielle Brunette & Christophe François & Antoine Leblois & Nicolas Martin-StPaul, 2021. "Index insurance for coping with drought-induced risk of production losses in French forests," Working Papers of BETA 2021-44, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    9. Brunette, M. & Holecy, J. & Sedliak, M. & Tucek, J. & Hanewinkel, M., 2015. "An actuarial model of forest insurance against multiple natural hazards in fir (Abies Alba Mill.) stands in Slovakia," Forest Policy and Economics, Elsevier, vol. 55(C), pages 46-57.
    10. Baoling Zou & Zanjie Ren & Ashok K. Mishra & Stefan Hirsch, 2022. "The role of agricultural insurance in boosting agricultural output: An aggregate analysis from Chinese provinces," Agribusiness, John Wiley & Sons, Ltd., vol. 38(4), pages 923-945, October.
    11. M. Brunette & S. Couture & J. Foncel & S. Garcia, 2020. "The decision to insure against forest fire risk: an econometric analysis combining hypothetical real data," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 45(1), pages 111-133, January.
    12. Sauter, Philipp A. & Möllmann, Torsten B. & Anastassiadis, Friederike & Mußhoff, Oliver & Möhring, Bernhard, 2016. "To insure or not to insure? Analysis of foresters' willingness-to-pay for fire and storm insurance," Forest Policy and Economics, Elsevier, vol. 73(C), pages 78-89.
    13. Sacchelli, Sandro & Cipollaro, Maria & Fabbrizzi, Sara, 2018. "A GIS-based model for multiscale forest insurance analysis: The Italian case study," Forest Policy and Economics, Elsevier, vol. 92(C), pages 106-118.
    14. Qin, Tao & Gu, Xuesong & Tian, Zhiwei & Pan, Huanxue & Deng, Jing & Wan, Li, 2016. "An empirical analysis of the factors influencing farmer demand for forest insurance: Based on surveys from Lin’an County in Zhejiang Province of China," Journal of Forest Economics, Elsevier, vol. 24(C), pages 37-51.

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