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农业供应链的稳健最优契约

Robustly Optimal Contracts for Agricultural Supply Chains
Management Science · 2025 · Zhaolin Li、Guitian Liang

中文摘要

由于种种因素(如缺乏足够的统计知识或数据、不可预见的天气事件),农产品的产量往往表现出高度的模糊性。当面临产量分布的模糊性时,农民与土地所有者可能基于均值和方差等描述性统计量作出缔约决策。为考察有限信息如何重塑最优契约形式,我们考虑这样一个农业供应链:土地所有者提供农田,一名有技能的农民付出有成本的私人努力来种植作物。双方均面临作物产量分布的模糊性,并采用稳健的最大-最小(max-min)决策规则。当土地所有者拥有起草契约的议价能力时(L 模型),我们发现债务与股权的混合契约是稳健最优的。相反,当农民拥有议价能力时(F 模型),最优契约可能是线性(股权)契约或非线性二次债务契约,取决于变异系数(CV)与土地所有者的保留利润。我们利用美国农业部数据校准模型,发现随着 CV 的增大,拥有议价能力的一方倾向于分担更多风险。我们还发现,当 CV 与土地所有者的保留利润均足够大时,L 模型会引致更高的努力水平;否则,F 模型实现更好的努力水平。最后,我们将模型加以扩展,以考虑随机作物价格、农民风险厌恶与有界作物产量等特征。

Abstract

Because of various factors (such as a lack of adequate statistical knowledge or data, unforeseen weather events), the yields of agricultural products often exhibit a high level of ambiguity. When facing distributional ambiguity in yields, farmers and landowners may base their contracting decisions on descriptive statistics, such as the mean and variance. To investigate how limited information could reshape optimal contract forms, we consider an agricultural supply chain in which a landowner contributes farmland and a skilled farmer exerts costly private effort to cultivate a crop. Both parties face distributional ambiguity in crop yield and employ a robust max-min decision rule. When the landowner possesses the bargaining power to draft the contract (the L model), we find that a hybrid contract of debt and equity is robustly optimal. In contrast, when the farmer possesses the bargaining power (the F model), the optimal contract could be a linear (equity) contract or a nonlinear quadratic debt contract, depending on the coefficient of variation (CV) and the landowner’s reservation profit. We use U.S. Department of Agriculture data to calibrate the model and find that, as the CV increases, the party that possesses the bargaining power tends to share more risk. We also find that when both the CV and the landowner’s reservation profit are sufficiently large, the L model induces a higher effort level; otherwise, the F model achieves better effort. Finally, we extend the model to consider various features, such as random crop price, farmer’s risk aversion and bounded crop yield.
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