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A System Dynamics Model Of Agriculture And Rural Development: The Topmard Core Model

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  • Johnson, Thomas G.
  • Bryden, John Marshall
  • Refsgaard, Karen
  • Alva Lizarraga, Sara

Abstract

The goal of the TOPMARD project is to develop a model of agriculture and rural development to better understand the agronomic, ecological, economic and social dimensions of rural regions. The resulting model, (Policy Model of Multifunctional Agriculture and Rural Development) was built collaboratively and hierarchically by the research teams from the 11 countries. The model features eight subsectors (Land, Agriculture, Tourism, Region, Human Resources, Non-commodities, Capital, and Quality of Life). Imbedded in the model are a complete dynamic input-output model, and an agecohort education demographic model. The model has both supply-side and demand-side drivers. Land use is the key supply-side driver. Land use, coupled with production system choices, determine agricultural and non-commodity outputs. The Quality of Life sector incorporates the coefficients from a regression analysis of migration behaviour to develop a supply-side population response to local quality of life which is added to the demand-side response to job growth.

Suggested Citation

  • Johnson, Thomas G. & Bryden, John Marshall & Refsgaard, Karen & Alva Lizarraga, Sara, 2008. "A System Dynamics Model Of Agriculture And Rural Development: The Topmard Core Model," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6497, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaa107:6497
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    File URL: http://purl.umn.edu/6497
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    References listed on IDEAS

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    1. A. Charnes & W. W. Cooper & E. Rhodes, 1981. "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through," Management Science, INFORMS, vol. 27(6), pages 668-697, June.
    2. Korhonen, Pekka J. & Luptacik, Mikulas, 2004. "Eco-efficiency analysis of power plants: An extension of data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 437-446, April.
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