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Hedging weather risk for corn production in Northeastern China

Author

Listed:
  • Baojing Sun
  • Changhao Guo
  • G. Cornelis van Kooten

Abstract

Purpose - – The paper analyzes the hedging efficiency of weather-indexed insurance for corn production in Northeast of China. The purpose of this paper is to identify the potential weather variables that impact corn yields and to analyze the efficiency of weather-indexed insurance under varying thresholds for payouts (strike values). Design/methodology/approach - – Statistical relationships between climate variables and crop yields are used to construct weather-indexed insurance that enable a farmer to hedge against adverse precipitation outcomes. Mean root square loss is used to compare the efficiency of various weather products. Findings - – Based on efficiency comparisons, it turns out that in some, but not all circumstances, cumulative rainfall (CR) insurance can be used to hedge weather risk. When CR explains one-third or more of the variation in corn yields, a hedge can offset the revenue loss caused by the corresponding weather risk; but when it explains much less of the yield variation, it is inefficient for hedgers to buy weather insurance. If CR explains variation in crop yields, it is increasingly efficient to employ CR-indexed insurance as strike values decline for put options or increase for call options. Practical implications - – The paper provides a method for calculating the premium for an insurance product that provides a payout if CR in a growing season is too low. Originality/value - – This research is important because it illustrates the potential benefits of using weather insurance as an agricultural risk management strategy in China.

Suggested Citation

  • Baojing Sun & Changhao Guo & G. Cornelis van Kooten, 2014. "Hedging weather risk for corn production in Northeastern China," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 74(4), pages 555-572, October.
  • Handle: RePEc:eme:afrpps:v:74:y:2014:i:4:p:555-572
    DOI: 10.1108/AFR-01-2014-0001
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    Citations

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    Cited by:

    1. Lu Zong & Manuela Ender, 2016. "Spatially-Aggregated Temperature Derivatives: Agricultural Risk Management in China," IJFS, MDPI, vol. 4(3), pages 1-17, September.

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