Modeling Agricultural Supply Response Using Mathematical Programming and Crop Mixes
扩展了历史作物组合方法，通过供给反应弹性和系统变化商品价格生成合成作物组合，以避免极端专业化，并应用于美国生物燃料政策分析。
Mathematical programming models are widely used in agricultural sector analysis. However, the lack of micro‐level data, as well as computational requirements, necessitate the aggregation of individual producers into representative units when working at the sectoral level. This usually leads to unrealistic extreme specialization in supply responses. In 1982, McCarl introduced the “historical crop mixes” approach to avoid extreme specialization. We extend this approach by generating additional synthetic crop mixes using supply response elasticities and systematically varied commodity prices. In addition to avoiding extreme specialization, this approach provides flexibility when future supply responses can be vastly different from past responses. An application to U.S. biofuel policy analysis is presented.