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Spatial Resource Management under Pollution Externalities

Listed author(s):
  • Anastasios Xepapadeas
  • Athanasios Yannacopoulos

Variables describing the state of an environmental system such as resources (renewable or exhaustible), pollutants, greenhouse gases have a profound spatial dimension. This is because resources or pollutants are harvested, extracted, emitted, or abated in a specific location or locations, the impacts of environmental variables, whether beneficial or detrimental, have a strong spatial dimension, and there is transport of environmental state variables across geographical space due to natural processes. In this paper we study dynamic optimization for the joint management of resources and pollution when pollution affects resource growth and when spatial transport phenomena both for the resources and the pollution are present. We present approaches that deal with dynamic optimization in infinite dimensional spaces which can be used as tools in environmental and resource economic. We also present methods which can be used to study the emergence of spatial patterns in dynamic optimizations models. Our methods draw on the celebrated Turing diffusion induced instability but are different from Turing�s mechanism since they apply to forward-optimization models. We believe that this approach provides the tools to analyze a wide range of problems with explicit spatial structure which are very often encountered in environmental and resource economics.

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File URL: http://wpa.deos.aueb.gr/docs/Spatial.Resource.Management.under.Pollution.Externalities.pdf
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Paper provided by Athens University of Economics and Business in its series DEOS Working Papers with number 1516.

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Date of creation: 29 Oct 2015
Handle: RePEc:aue:wpaper:1516
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  1. James E. Wilen, 2007. "Economics of Spatial-Dynamic Processes," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(5), pages 1134-1144.
  2. Camacho, Carmen & Pérez-Barahona, Agustín, 2015. "Land use dynamics and the environment," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 96-118.
  3. John Hassler & Per Krusell, 2012. "Economics And Climate Change: Integrated Assessment In A Multi-Region World," Journal of the European Economic Association, European Economic Association, vol. 10(5), pages 974-1000, October.
  4. Brock, William A. & Xepapadeas, Anastasios & Yannacopoulos, Athanasios N., 2014. "Spatial externalities and agglomeration in a competitive industry," Journal of Economic Dynamics and Control, Elsevier, vol. 42(C), pages 143-174.
  5. Desmet, Klaus & Rossi-Hansberg, Esteban, 2015. "On the spatial economic impact of global warming," Journal of Urban Economics, Elsevier, vol. 88(C), pages 16-37.
  6. Klaus Desmet & Esteban Rossi-Hansberg, 2010. "On Spatial Dynamics," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 43-63.
  7. Behringer, Stefan & Upmann, Thorsten, 2014. "Optimal harvesting of a spatial renewable resource," Journal of Economic Dynamics and Control, Elsevier, vol. 42(C), pages 105-120.
  8. Smith, Martin D. & Sanchirico, James N. & Wilen, James E., 2009. "The economics of spatial-dynamic processes: Applications to renewable resources," Journal of Environmental Economics and Management, Elsevier, vol. 57(1), pages 104-121, January.
  9. Brock, William A. & Engström, Gustav & Grass, Dieter & Xepapadeas, Anastasios, 2013. "Energy balance climate models and general equilibrium optimal mitigation policies," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2371-2396.
  10. W.A. Brock & A. Xepapadeas & A.N. Yannacopoulos, 2014. "Optimal Control in Space and Time and the Management of Environmental Resources," Annual Review of Resource Economics, Annual Reviews, vol. 6(1), pages 33-68, October.
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