Abstract
Mathematical programming models are widely used in agricultural sector analysis. Lack of micro-level data and computational reasons necessitate aggregation of individual producers into regional representative units when working at sectoral level. This usually leads to unrealistic and extreme specialization in supply responses. McCarl (1982) introduced the ‘historical crop mixes’ approach to avoid extreme specialization. This paper extends the crop mix approach by generating additional synthetic crop mixes based on estimated supply response elasticities and systematically varied market prices. While avoiding extreme specialization this approach provides sufficient flexibility when future supply responses can be drastically different from past responses.
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