Mathematical programming models of farmers’ cropping decisions must first be calibrated before they can be used to examine agricultural producer responses to policy changes. In this paper, we compare three calibration approaches for disentangling the risk parameter from the parameters of the cost function: one assumes a logarithmic utility function, while the others employ an exponential utility function. Historical crop insurance data for southern Alberta, Canada, are used to assess the calibration performance of the three approaches, and sensitivity analysis is implemented to test whether the changes in the optimal land allocation caused by the changes in the values of the parameters are practically reasonable. Only one of the three models is of practical use for policy analysis because it can recover the true values of the parameters and the results of sensitivity analysis are reasonable.

中文翻译：

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使用正数学程序校准农业风险程序模型

必须首先校准农民的种植决策的数学程序设计模型，然后才能将其用于检查农业生产者对政策变化的反应。在本文中，我们比较了三种将风险参数与成本函数的参数区分开的校准方法：一种采用对数效用函数，而另一种采用指数效用函数。使用加拿大艾伯塔省南部的历史农作物保险数据评估这三种方法的校准性能，并进行敏感性分析，以测试由参数值的变化引起的最佳土地分配的变化在实际上是否合理。