Input Use Decisions with Greater Information on Crop Conditions: Implications for Insurance Moral Hazard and the Environment
研究了精准农业技术提供更准确的作物状况预测（即“预报”）如何影响投保和未投保农场的投入决策，发现预报准确度提高会减少长期道德风险，但可能增加赔付支出，并讨论了这对联邦作物保险计划和环境的影响。
Emerging precision agriculture technologies allow farms to make input decisions with greater information on crop conditions. This greater information occurs by providing improved predictions of crop yields using remote sensing and crop simulation models and by allowing farms to apply inputs within the growing season when some crop conditions are already realized. We use a stylized model with uncertainty in yield and price to examine how greater information on crop conditions (i.e., a “forecast”) affects input use for insured and uninsured farms. We show that moral hazard decreases—farms apply more inputs—as the forecast accuracy improves when the forecast indicates good yields, and vice versa when the forecast indicates bad yields. In the long run, moral hazard decreases in response to an improvement in forecast accuracy. Even though moral hazard decreases in the long run, indemnity payments are likely to increase in the long run—driven by the increase in moral hazard when the forecast indicates bad crop conditions. We use the results of our model to discuss the potential impact of different technologies and types of inputs on the federal crop insurance program and the environment.