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Specification of Environmental Emission Trading Options in a Spatial Multi-Agent Simulation Model of Pastoral Farming

Author

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  • Dake, Chris K.G.
  • Manderson, Andrew K.
  • MacKay, Alec D.

Abstract

A risk efficient frontier for a pastoral farm indicates the optimal enterprise mix that allows the farmer to generate the highest income for a given level of financial risk. It is calculated by matching the available range of enterprises (sheep, beef cattle, deer, dairy, exotic forest and indigenous forest) to the mix of land classes available on the farm. The quantity of environmental emissions produced from the farm varies with the optimal enterprise mix along the risk efficient frontier, and therefore enables the farmer to assess the financial consequences of moving along the frontier to achieve a desired level of environmental emissions. This study uses databases of land cover, land classes and farm boundaries to develop a method for estimating the risk efficient frontier for each farm in the Lake Taupo catchment. The information is used to develop nitrogen trading rules for farmers in a multi-agent simulation framework. The other decision makers in the multi-agent simulation framework are the regulatory institution which sets trading rules and can purchase nitrogen, and the auctioneer who manages the trading protocols. The regulator's cost function for acquiring nitrogen was derived assuming the regulator has full information of the risk efficient frontier of each farmer in the Lake Taupo catchment. Other trading protocols using complete or partial information of the farmers risk efficient frontiers are being developed.

Suggested Citation

  • Dake, Chris K.G. & Manderson, Andrew K. & MacKay, Alec D., 2006. "Specification of Environmental Emission Trading Options in a Spatial Multi-Agent Simulation Model of Pastoral Farming," 2006 Conference, August 24-25, 2006, Nelson, New Zealand 31968, New Zealand Agricultural and Resource Economics Society.
    • Handle: RePEc:ags:nzasin:31968
    DOI: 10.22004/ag.econ.31968
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