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  • 标题:Managing Irrigation Risk with Inflow-Based Derivatives: The Case of Rio Mayo Irrigation District in Sonora, Mexico
  • 本地全文:下载
  • 作者:Leiva, Akssell J. ; Skees, Jerry R.
  • 期刊名称:Journal of Food Distribution Research
  • 印刷版ISSN:0047-245X
  • 出版年度:2005
  • 期号:SUPPL
  • 出版社:Food Distribution Research Society
  • 摘要:Uncertain reservoir inflows represent a major source of risk for irrigated agriculture. A derivative instrument that uses reservoir inflows as the underlying variable is designed and tested with a recursive stochastic simulation of the Rio Mayo irrigations system. The results indicate that the instrument effectively protects against downside risk.
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