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The importance of farmer behaviour: an application of Desktop MAS, a multi-agent system model for rural New Zealand communities

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Author Info

  • Schilling, Chris
  • Kaye-Blake, William
  • Post, Elizabeth
  • Rains, Scott

Abstract

This paper describes a multi-agent system (MAS) model, Desktop MAS, designed for New Zealand‟s pastoral industries. Desktop MAS models the strategic decisions and behaviours of individual farmers in response to changes in their operating environment. Farmer responses determine production, economic and environmental outcomes. Each farmer has a profit-maximising or cost-minimising objective that governs their decision-making, and a social network with whom they interact. Information transfer between farmers occurs through this social network. We consider a simple scenario analysis that investigates the impact of emissions prices on industry mix and farming intensity. We then investigate the importance of farmer behaviours and interaction. We find that farmer social networks and objectives impact particularly on farming intensity decisions within land-use industries. Land-use change between industries becomes more sensitive to farmer attitudes as the profitability differential between land-uses narrows.

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Bibliographic Info

Paper provided by New Zealand Agricultural and Resource Economics Society in its series 2012 Conference, August 31, 2012, Nelson, New Zealand with number 136070.

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Date of creation: Aug 2012
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Handle: RePEc:ags:nzar12:136070

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Web page: http://www.nzares.org.nz/
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Related research

Keywords: Agribusiness; Community/Rural/Urban Development; Farm Management; Land Economics/Use; Production Economics;

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  1. Happe, Kathrin & Balmann, Alfons, 2008. "Doing Policy In The Lab! Options For The Future Use Of Model-Based Policy Analysis For Complex Decision-Making," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6588, European Association of Agricultural Economists.
  2. Happe, Kathrin & Balmann, Alfons & Kellermann, Konrad, 2004. "The agricultural policy simulator (AgriPoliS): an agent-based model to study structural change in agriculture (Version 1.0)," IAMO Discussion Papers 71, Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO).
  3. Berger, Thomas & Schreinemachers, Pepijn & Woelcke, Johannes, 2006. "Multi-agent simulation for the targeting of development policies in less-favored areas," Agricultural Systems, Elsevier, vol. 88(1), pages 28-43, April.
  4. Balmann, Alfons, 1997. "Farm-Based Modelling of Regional Structural Change: A Cellular Automata Approach," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 24(1), pages 85-108.
  5. Alfons Balmann, Kathrin Happe, Konrad Kellermann, Anne Kleingarn, 2001. "Adjustment Costs of Agri-Environmental Policy Switchings: A Multi-Agent Approach," Computing in Economics and Finance 2001 148, Society for Computational Economics.
  6. Suzi Kerr & Alex Olssen, 2012. "Gradual Land-use Change in New Zealand: Results from a Dynamic Econometric Model," Working Papers 12-06, Motu Economic and Public Policy Research.
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