Switching to Perennial Energy Crops Under Uncertainty and Costly Reversibility
研究了农民在考虑沉没成本、收益不确定性和学习效应时，将传统耕地转为能源作物的决策，发现最优规则与忽略学习的净现值规则及仅允许单向转换的实物期权模型显著不同，并以玉米-大豆轮作和柳枝稷为例展示了模型预测对收益随机过程的敏感性。
We study a farmer's decision to convert traditional crop land into growing dedicated energy crops, taking in account sunk conversion costs, uncertainties in traditional and energy crop returns, and learning.The optimal decision rules differ significantly from the expected net present value rule, which ignores learning, and from real option models that allow only one way conversions into energy crops.These models also predict drastically different patterns of land conversions into and out of energy crops over time.Using corn-soybean rotations and switchgrass as examples, we show that the model predictions are sensitive to assumptions about stochastic processes of the returns.Government policies might have unintended consequences: subsidizing conversion costs into switchgrass reduces proportions of land in switchgrass in the long run.