Plant growth stages and weather index insurance design

被引:2
|
作者
Zou, Jing [1 ]
Odening, Martin [2 ]
Okhrin, Ostap [1 ,3 ]
机构
[1] Tech Univ Dresden, Friedrich List Fac Transportat, Chair Stat & Econometr, Dresden, Germany
[2] Humboldt Univ, Dept Agr Econ, Farm Management Grp, Berlin, Germany
[3] Ctr Scalable Data Analyt & Artificial Intelligence, Leipzig, Germany
关键词
Weather index insurance; nonlinear indemnity; plant growth stages; generalized additive model; PS-ANOVA; CROP INSURANCE; YIELD RISK; P-SPLINES; MODELS; DERIVATIVES; DROUGHT; PRECIPITATION; SENSITIVITY; PERSPECTIVE; EFFICIENCY;
D O I
10.1017/S1748499523000167
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Given the assumption that weather risks affect crop yields, we designed a weather index insurance product for soybean producers in the US state of Illinois. By separating the entire vegetation cycle into four growth stages, we investigate whether the phase-division procedure contributes to weather-yield loss relation estimation and, hence, to basis risk mitigation. Concretely, supposing stage-variant interaction patterns between temperature-based weather index growing degree days and rainfall-based weather index cumulative rainfall, a nonparametric weather-yield loss relation is estimated by a generalized additive model. The model includes penalized B-spline (P-spline) approach based on nonlinear optimal indemnity solutions under the expected utility framework. The P-spline analysis of variance (PS-ANOVA) method is used for efficient estimation through mixed model re-parameterization. The results indicate that the phase-division models significantly outperform the benchmark whole-cycle ones either under quadratic utility or exponential utility, given different levels of risk aversions. Finally, regarding hedging effectiveness, the expected utility ratio between the phase-division contract and the whole-cycle contract, and the percentage changes of mean root square loss and variance of revenues support the proposed phase-division contract.
引用
收藏
页码:438 / 458
页数:21
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