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The spatial dimension in environmental and resource economics




Mechanisms generating patterns in spatial domains have been extensively studied in biology, but also in economics in the context of new economic geography. The Turing mechanism or Turing diffusion-induced instability has been central to the understanding of forces which endogenously generate spatial patterns, but in a context where agents do not explicitly optimize an objective. The present paper reviews tools to study, in the spirit of Turing's analysis, a mechanism generating optimal diffusion-induced instability where optimizing agents generate optimal agglomerations. By extending the maximum principle to the optimal control of partial differential equations, it is shown how under certain conditions it will be optimal to design controls so that the price-quantity system implied by the costate–state functions of the optimal control of distributed parameter systems induces optimal spatial patterns. These methods might be useful in studying pattern formation both in problems of resource management and of economic development.

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  • Xepapadeas, Anastasios, 2010. "The spatial dimension in environmental and resource economics," Environment and Development Economics, Cambridge University Press, vol. 15(06), pages 747-758, December.
  • Handle: RePEc:cup:endeec:v:15:y:2010:i:06:p:747-758_00

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    References listed on IDEAS

    1. Karl-Göran Mäler, 2008. "Sustainable Development and Resilience in Ecosystems," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 39(1), pages 17-24, January.
    2. Brian Walker & Leonie Pearson & Michael Harris & Karl-Göran Maler & Chuan-Zhong Li & Reinette Biggs & Tim Baynes, 2010. "Incorporating Resilience in the Assessment of Inclusive Wealth: An Example from South East Australia," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 45(2), pages 183-202, February.
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    Cited by:

    1. Javier de Frutos & Guiomar Martín-Herrán, 2016. "Pollution control in a multiregional setting: a differential game with spatially distributed controls," Gecomplexity Discussion Paper Series 201601, Action IS1104 "The EU in the new complex geography of economic systems: models, tools and policy evaluation", revised Jan 2016.
    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. W. A. Brock & A. Xepapadeas, 2015. "Modeling Coupled Climate, Ecosystems, and Economic Systems," Working Papers 2015.66, Fondazione Eni Enrico Mattei.
    4. Anastasios Xepapadeas, "undated". "Diffusion and Spatial Aspects," DEOS Working Papers 1232, Athens University of Economics and Business.
    5. Eli Fenichel & Timothy Richards & David Shanafelt, 2014. "The Control of Invasive Species on Private Property with Neighbor-to-Neighbor Spillovers," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(2), pages 231-255, October.
    6. Ballestra, Luca Vincenzo, 2016. "The spatial AK model and the Pontryagin maximum principle," Journal of Mathematical Economics, Elsevier, vol. 67(C), pages 87-94.

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