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Location choice for renewable resource extraction with multiple non-cooperative extractors: a spatial Nash equilibrium model and numerical implementation

Sterner, E. O., Robinson, E. J. Z. and Albers, H. J. (2018) Location choice for renewable resource extraction with multiple non-cooperative extractors: a spatial Nash equilibrium model and numerical implementation. Letters in Spatial and Resource Sciences, 11 (3). pp. 315-331. ISSN 1864-404X

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To link to this item DOI: 10.1007/s12076-018-0215-4

Abstract/Summary

Especially in lower-income countries, the distribution of renewable resources in open access settings often reflects the non-cooperative spatial extraction decisions of many individuals who spread out across a landscape. These individuals recognize tradeoffs between distance to the resource, density, and competition amongst extractors. In this paper we present a game theoretic model that explicitly accommodates such explicitly spatial non-cooperative behavior with respect to the extraction of a stationary renewable natural resource, such as a non-timber forest products or bivalvia (for example, oysters, clams), that is located in a two dimensional landscape. Villagers that have identical labor allocations and preferences are shown to undertake very different extraction pathways in equilibrium. For example, some may extract in more congested patches closer to the village while others may extract in less crowded but more distant patches. For many parameterizations, we find multiple spatial Nash equilibria that differ with respect to the number of villagers at each resource location, whether individual villagers extract from one or multiple locations, and the extent and spatial pattern of resource degradation. In addition to finding equilibria with widely different actions taken by identical extractors, the analysis here demonstrates the impact of simplifying assumptions for spatial decisions on predictions of policy impact, resource distributions, and conflict.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Life Sciences > School of Agriculture, Policy and Development > Economic and Social Sciences Division > Food Economics and Marketing (FEM)
ID Code:77799
Publisher:Springer

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