Modeling agricultural supply response using mathematical programming and crop mixes

Xiaoguang Chen, Hayri Önal

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)674-686
Number of pages13
JournalAmerican Journal of Agricultural Economics
Issue number3
StatePublished - Apr 2012


  • Aggregation
  • Agricultural supply response
  • Crop mixes
  • Mathematical programming
  • Synthetic mixes

ASJC Scopus subject areas

  • Agricultural and Biological Sciences (miscellaneous)
  • Economics and Econometrics


Dive into the research topics of 'Modeling agricultural supply response using mathematical programming and crop mixes'. Together they form a unique fingerprint.

Cite this