Theoretical and Applied Climatology

, Volume 111, Issue 3–4, pp 713–728 | Cite as

Design of agricultural insurance policy for tea tree freezing damage in Zhejiang Province, China

Original Paper
First Online:
Received:
Accepted:

Abstract

This paper proposes a method to design freezing damage policy-based agricultural insurance contracts for tea trees (an economic crop) in the Zhejiang Province of China, using a weather index. Data of economic losses caused by freezing damage, and the beginning dates of tea plucking (BDTP) from the Agricultural Bureau of each county in Zhejiang Province and tea planters, and meteorological observations were collected to establish the prediction model for BDTP, and to determine the relationship between economic loss rates caused by freezing damage at or before BDTP, and the minimum temperatures for “Wuniuzao,” “Longjing-43,” and “Jiukeng” teas. Based on the information diffusion theoretical model, occurrence probabilities of BDTP from 1 February to 20 April and lower temperatures at different levels are calculated. Then, the insurance premium rates of the three tea tree species can be estimated. Lastly, the tea tree freezing damage insurance contracts are designed, combining the advantages of regional yield-based index insurance and weather-based index insurance.

Keywords

Agricultural Insurance Premium Rate Claim Amount Index Insurance Weather Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access.

Notes

Acknowledgments

This paper was financially supported by a major agricultural project from Science Technology Department of Zhejiang Province, China (grant no. 2011C22082) and a major project from Zhejiang Province Meteorological Administration, China (grant no. 2010ZD07). The authors would like to thank all the data-providing agencies and bodies.

References

  1. Barry KG, Alan PK (1998) Nonparametric estimation of crop yield distributions: implications for rating group-risk crop insurance contracts. Am J Agric Econ 80:139–153CrossRefGoogle Scholar
  2. Barry JB, Olivier M (2007) Weather index insurance for agriculture and rural areas in lower-income countries. Am J Agric Econ 89:1241–1247CrossRefGoogle Scholar
  3. Botts RR, Boles JN (1958) Use of normal-curve theory in crop insurance rate making. J Farm Econ 40:733–740CrossRefGoogle Scholar
  4. Chantarat C, Barrett CB, Mude AG, Turvey CG (2007) Using weather index insurance to improve drought response for famine prevention. Am J Agric Econ 89:1262–1268CrossRefGoogle Scholar
  5. China Tea Marketing Association (2010) Production and sales analysis of China spring tea in 2010. China Tea 40(6):6–7 (in Chinese)Google Scholar
  6. Ding G, Wu K, Yi Z (2008) Investigation of agricultural insurance in Heilongjiang and Jiling. China Financ 53:41–43 (in Chinese)Google Scholar
  7. Du G, Wang G (2002) Researchof China agricultural insurance and social security system in rural areas. Capital Economic University Press, Beijing, pp 1–15 (in Chinese)Google Scholar
  8. Featherstone AM, Kastens TL (2000) Non-parametric and semi-parametric techniques for modeling and simulating correlated, non-normal price and yield distributions: applications to risk analysis in Kansas agriculture. J Agric Appl Econ 32:267–281Google Scholar
  9. Geyser JM (2004) Weather derivatives: concept and application for their use in South Africa. Agrekon 43:444–464CrossRefGoogle Scholar
  10. Glauber JW (2004) Crop insurance reconsidered. Am J Agric Econ 86:1179–1195CrossRefGoogle Scholar
  11. Global AgRisk (2009) Designing agricultural index insurance in developing countries: a global AgRisk market development model hand book for policy and decision makers. Global AgRisk, Lexington, pp 12–13Google Scholar
  12. Goodwin BK, Roberts MC, Coble KH (2000) Measurement of price risk in revenue insurance: implications of distributional assumptions. J Agric Resour Econ 25:195–214Google Scholar
  13. Gunnar B, Raushan B, Olaf H (2008) Evaluating the potential of index insurance schemes to reduce crop yield risk in an arid region. J Agric Econ 59:312–328CrossRefGoogle Scholar
  14. Helene LB, Xavier G, Robert T, James V (2005) Weather insurance in semi-arid India. Paper presented in securing development in an Unstable World: Annual Bank Conference on Development Economics 2005, in Amsterdam, The NetherlandsGoogle Scholar
  15. Huang S (1989) Meteorology of the tea plant in China: a review. Agric For Meteorol 47:19–30CrossRefGoogle Scholar
  16. Huang C, Moraga C (2005) Extracting fuzzy if–then rules by using the information matrix technique. J Comput Syst Sci 70:26–52CrossRefGoogle Scholar
  17. Jones TL (2007) Agricultural applications of weather derivatives. Int Bus Econ Res J 6:53–60Google Scholar
  18. Just RE, Weninger Q (1999) Are crop yields normally distributed? Am J Agric Econ 81:287–304CrossRefGoogle Scholar
  19. Ker A, Goodwin B (1995) Rating and yield predicting procedures for the group risk federal crop insurance program. Progress Report delivered to Federal Crop Insurance CorporationGoogle Scholar
  20. Ker AP, Goodwin BK (2000) Nonparametric estimation of crop insurance rates revisited. Am J Agric Econ 83:463–478CrossRefGoogle Scholar
  21. Liu X, Zhang J, Cai W, Tong Z (2010) Information diffusion-based spatio-temporal risk analysis of grassland fire disaster in northern China. Knowl-Based Syst 23:53–60CrossRefGoogle Scholar
  22. Lou W (1996) Analysis of weather conditions of tea production in Xinchang County. J Zhejiang Meteorol 17:34–36 (in Chinese)Google Scholar
  23. Lou W, Wu L, Chen H, Mao Y (2010) Analysis and design of premium rates determined for weather-based index insurance on tract of citrus. Sci Agric Sin (A Sankarasubramanian 2003) 43:1904–1911 (in Chinese)Google Scholar
  24. Miranda MJ (1991) Area–yield crop insurance reconsidered. Am J Agric Econ 73:233–242CrossRefGoogle Scholar
  25. Miranda M, Vedenov DV (2001) Innovations in agricultural and natural disaster insurance. Am J Agric Econ 83:650–655CrossRefGoogle Scholar
  26. Motha RP (2007) Development of an agricultural weather policy. Agric For Meteorol 142:303–313CrossRefGoogle Scholar
  27. Ozaki VA, Ghosh SK, Goodwin BK, Shirota R (2008) Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts. Am J Agric Econ 90:951–961CrossRefGoogle Scholar
  28. Pi L, Li J (2003) Analysis of insurance needs and commercial supply of China’s new economic development stage in rural areas. China Rural Econ 19:68–75 (in Chinese)Google Scholar
  29. Ramirez OA, Misra SK, Nelson J (2003) Efficient estimation of agricultural time series models with non-normal dependent variables. Am J Agric Econ 85:1029–1040CrossRefGoogle Scholar
  30. Sherrick BJ, Zanini FC, Schnitkey DG, Irwin SH (2004) Crop insurance valuation under alternative yield distributions. Am J Agric Econ 86:406–419CrossRefGoogle Scholar
  31. Smith VH (2003) Federal crop and crop revenue insurance programs: income protection. Agricultural Economics & Economics, Briefing No.11Google Scholar
  32. Smith VH, Chouinard HH, Baquet AE (1994) Almost ideal area yield crop insurance contracts. Agric Resour Econ Rev 23:75–83Google Scholar
  33. Wang H, Wang B, Bao J (1981) Statistical methods of threshold temperature and accumulated temperature of Camellia sinensis sprouting in spring. Chin J Agrometeorol 3:65–70 (in Chinese)Google Scholar
  34. Wenner M, Arias D (2003) Agricultural insurance in Latin American: where are we? Paving the way forward for rural finance. An international conference on best practices. International Trade Center, Washington, pp 1–18Google Scholar
  35. Yang CC, Brockett PL, Wen MM (2009) Basis risk and hedging efficiency of weather derivatives. J Risk Financ 10:517–536CrossRefGoogle Scholar
  36. Zeng L (2000) Weather derivatives and weather insurance: concept, application, and analysis. Bull Am Meteorol Soc 81:2075–2082CrossRefGoogle Scholar
  37. Zhang X, Qian J (2010) Frost characteristics and its effect on agriculture in Taiyuan under climate warming. Chin J Agrometeorol 32(1):111–114, 120. (in Chinese)Google Scholar
  38. Zhang Y, Gu H, Shi Q (2006) The review and reconsideration of China agricultural insurance system research since 1935. Probl Agric Econ 27:43–47 (in Chinese)Google Scholar
  39. Zhejiang Tea Industry Association (2011) Production and sales analysis of China tea in 2010. China Tea 40(5):20–21 (in Chinese)Google Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  1. 1.Xinchang Weather BureauXinchang CountyChina
  2. 2.Applied Hydrometeorological Research InstituteNanjing University of Information Science & Technology (NUIST)NanjingChina

Personalised recommendations