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The Application and Modification of Delegation-Agent Model in Agricultural Insurance
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作者 xue hai-lian ZHANG Hai-xia 《Asian Agricultural Research》 2010年第8期17-18,22,共3页
The delegation-agent models in agricultural insurance are established both under the circumstances of information symmetry and information asymmetry.Insurers choose effort level-a* according to the first order optimal... The delegation-agent models in agricultural insurance are established both under the circumstances of information symmetry and information asymmetry.Insurers choose effort level-a* according to the first order optimal condition of ∫{v(π-s(π))+λ11[u(s(π))]fa(π,a*)}dπ=λ11c'(a*)u(s(π)) at the present stage when the information is symmetric.While the information is asymmetric,the first order optimal condition changed into v'(π-s(π))u'(s(π))=λ21+μ21(1-fa(π,a)f(π,a)).In other words,the higher the output,the more and more income of insured.The paper also modifies the models,when the information is symmetric,the insurers determine the effort level of insured-a* based on the first order optimal condition of ∫{v(π-s(π))+λ12[u(s(π))]fa(π,a*)}dπ=λ12h'(a*)u(s(π));to the contrary,the first order optimal condition would change into v'(π*-s(π*))u'(s(π*))=λ22+μ22(1-fa(π,a)f(π,a))-λh(a)f(π,a)-μh'(a)f(π,a).The results show that the insured and the insurers would both benefit from the insurance when the effort cost function related to the expectation of the insured(agricultural producers).If the insured manage the objects of insurance more seriously,the rate of disasters would be lowered.Therefore,the insurance claimed against the insured would be lessened,and the benefits of the insurers would be increased at last. 展开更多
关键词 Agricultural insurance Delegation-agent model Moral hazard MODIFICATION China
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基于过程模型CROBAS的全局灵敏度分析方法比较
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作者 薛海连 田相林 +2 位作者 王彬 孙帅超 曹田健 《应用生态学报》 CAS CSCD 北大核心 2021年第1期134-144,共11页
过程机理模型在开发过程中常受限于生理学参数无法直接或准确测量。全局灵敏度分析可以评估模型预测结果对于生理学参数变化的响应,为模型结构改进、数据收集和参数校准提供参考。本研究基于过程模型CROBAS,以华山松为例,选取模型中描... 过程机理模型在开发过程中常受限于生理学参数无法直接或准确测量。全局灵敏度分析可以评估模型预测结果对于生理学参数变化的响应,为模型结构改进、数据收集和参数校准提供参考。本研究基于过程模型CROBAS,以华山松为例,选取模型中描述树木结构关系的10个参数,以树高和各器官生物量的Nash-Sutcliffe效率(NSE)为目标函数,比较了3种应用较广泛的全局灵敏度分析方法,即Morris筛选法、基于方差的Sobol指数法和扩展的傅里叶幅度检验法(EFAST)。结果表明:参数灵敏度排序在不同方法中仅略微有所变化,但对于不同目标函数则区别明显。对算法耗时和收敛效率而言,Morris和EFAST性能较高,Sobol效率相对较低。所有模型输出变量均对单位面积年最大光合速率、比叶面积、消光系数敏感,林冠光截留状态对于林木生长量有着关键性影响,意味着光合固碳量是CROBAS在模型校正和林木生长动态模拟中需要优先进行数据收集、验证与测试的模块。灵敏度分析同时表明,碳平衡理论在林木生物量模拟中最为核心部分是树叶生物量模块的计算与验证。对于复杂过程模型的参数灵敏度分析,如需定性研究可选Morris,而量化评估采用EFAST更适合。 展开更多
关键词 过程模型 全局灵敏度 MORRIS Sobol EFAST
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