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Evaluating agricultural catastrophic risk

Author

Listed:
  • Lei Xu
  • Qiao Zhang
  • Xi Zhang

Abstract

Purpose - The purpose of this paper is to provide an evaluation method for agricultural catastrophic risk. Design/methodology/approach - Data on agricultural disaster loss are collected based on hectares covered by natural disasters, hectares affected by natural disasters, and hectares destroyed by natural disasters using the standard process. Peak over threshold (POT) approach based on the extreme value theory is used to model the distribution of agricultural catastrophic loss, and value at risk (VaR) is used to assess agricultural catastrophic risk. Findings - This paper provides an approach for collecting agricultural loss data and modelling probability distribution of agricultural catastrophic loss, which is promising for agricultural catastrophic risk evaluating. As the quantified measurement of agricultural catastrophic risk, VaR is observed to be appropriate and feasible. Results of empirical research demonstrate that drought catastrophe negatively affects grain‐production in the northeast region of China; in particular, the drought catastrophic risk is severe within a 100‐year scenario and thus is expected to recur. Originality/value - To provide an accurate agricultural catastrophic risk assessment, data collection based on disaster occurrence instead of crop yield, and VaR is used in this paper.

Suggested Citation

  • Lei Xu & Qiao Zhang & Xi Zhang, 2011. "Evaluating agricultural catastrophic risk," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 3(4), pages 451-461, November.
    • Handle: RePEc:eme:caerpp:v:3:y:2011:i:4:p:451-461
    DOI: 10.1108/17561371111192310
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    References listed on IDEAS

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    1. Alan P. Ker & Keith Coble, 2003. "Modeling Conditional Yield Densities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 291-304.
    2. Bruce J. Sherrick & Fabio C. Zanini & Gary D. Schnitkey & Scott H. Irwin, 2004. "Crop Insurance Valuation under Alternative Yield Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 406-419.
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    5. Goodwin, Barry K. & Mahul, Olivier, 2004. "Risk modeling concepts relating to the design and rating of agricultural insurance contracts," Policy Research Working Paper Series 3392, The World Bank.
    6. Octavio A. Ramirez & Sukant Misra & James Field, 2003. "Crop-Yield Distributions Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 108-120.
    7. 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.
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    Cited by:

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    2. Xiang Luo & Xinhai Lu & Zuo Zhang & Yue Pan, 2020. "Regional differences and rural public expenditure cyclicality: evidence from transitory and persistent shocks in China," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 65(2), pages 281-318, October.
    3. Cary, Michael A. & Frey, Gregory E., 2020. "Alley cropping as an alternative under changing climate and risk scenarios: A Monte-Carlo simulation approach," Agricultural Systems, Elsevier, vol. 185(C).

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