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Cited by 263

The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.

Resource Dependence, Economic Performance, and Political Stability

Dunning, Thad·2005·Journal of Conflict Resolution

Abstract

In many resource-dependent states, elites may face an important trade-off between the economic benefits of diversification and the possibility for future political competition that diversification may engender. However, distinctive features of global resource markets and national political economies may make diversification more or less attractive to political elites. The author argues that in three cases which illustrate the equilibrium paths of the game-theoretic model developed here—postindependence Bostwana, Mobutu’s Zaire, and Suharto’s Indonesia—three variables influenced elites’ incentives for diversification and thereby shaped outcomes along the dimensions of political stability and economic performance: the world market structure for the resource, the degree of societal opposition to elites, and the prior development of the nonresource private sector. These countries’ varied paths from resource wealth to political and economic outcomes suggest the need for conditional theories of the resource curse.

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Metadata

Authors
Dunning, T.
Venue
Journal of Conflict Resolution
Published
2005-08
Volume
49
Issue
4
Pages
451-482
ISSN
  • 0022-0027 (ISSN-L)
  • 1552-8766
OpenAlex
W2128956132
Cited by
263
References
63
FWCI
14.26
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Resource Dependence, Economic Performance, and Political Stability. https://app.cochat.ai/papers/10.1177/0022002705277521
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Dunning, T. (2005). Resource Dependence, Economic Performance, and Political Stability. Journal of Conflict Resolution. https://doi.org/10.1177/0022002705277521

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.