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Governing Social-Ecological Systems

In: Handbook of Computational Economics

Author

Listed:
  • Janssen, Marco A.
  • Ostrom, Elinor

Abstract

Social-ecological systems are complex adaptive systems where social and biophysical agents are interacting at multiple temporal and spatial scales. The main challenge for the study of governance of social-ecological systems is improving our understanding of the conditions under which cooperative solutions are sustained, how social actors can make robust decisions in the face of uncertainty and how the topology of interactions between social and biophysical actors affect governance. We review the contributions of agent-based modeling to these challenges for theoretical studies, studies which combines models with laboratory experiments and applications of practical case studies.Empirical studies from laboratory experiments and field work have challenged the predictions of the conventional model of the selfish rational agent for common pool resources and public-good games. Agent-based models have been used to test alternative models of decision-making which are more in line with the empirical record. Those models include bounded rationality, other regarding preferences and heterogeneity among the attributes of agents. Uncertainty and incomplete knowledge are directly related to the study of governance of social-ecological systems. Agent-based models have been developed to explore the consequences of incomplete knowledge and to identify adaptive responses that limited the undesirable consequences of uncertainties. Finally, the studies on the topology of agent interactions mainly focus on land use change, in which models of decision-making are combined with geographical information systems.Conventional approaches in environmental economics do not explicitly include non-convex dynamics of ecosystems, non-random interactions of agents, incomplete understanding, and empirically based models of behavior in collective action. Although agent-based modeling for social-ecological systems is in its infancy, it addresses the above features explicitly and is therefore potentially useful to address the current challenges in the study of governance of social-ecological systems.

Suggested Citation

  • Janssen, Marco A. & Ostrom, Elinor, 2006. "Governing Social-Ecological Systems," Handbook of Computational Economics,in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 30, pages 1465-1509 Elsevier.
  • Handle: RePEc:eee:hecchp:2-30
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    Cited by:

    1. Chang, Myong-Hun & Harrington, Joseph Jr., 2006. "Agent-Based Models of Organizations," Handbook of Computational Economics,in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 26, pages 1273-1337 Elsevier.
    2. Chanteau, Jean-Pierre & Labrousse, Agnès, 2013. "L’institutionnalisme méthodologique d’Elinor Ostrom : quelques enjeux et controverses," Revue de la Régulation - Capitalisme, institutions, pouvoirs, Association Recherche et Régulation, vol. 14.
    3. Carrasco, L. Roman & Cook, David & Baker, Richard & MacLeod, Alan & Knight, Jon D. & Mumford, John D., 2012. "Towards the integration of spread and economic impacts of biological invasions in a landscape of learning and imitating agents," Ecological Economics, Elsevier, vol. 76(C), pages 95-103.
    4. Dominique Ami & Juliette Rouchier, 2014. "Mesures techniques, Choix Institutionnels et Equité dans l’usage d’une ressource commune : Le cas du littoral marseillais," AMSE Working Papers 1427, Aix-Marseille School of Economics, Marseille, France, revised Jun 2014.
    5. Stefan Ambec & Alexis Garapin & Laurent Muller & Carine Sebi, 2009. "Règlementation acceptable d’une ressource commune : une analyse expérimentale," Économie et Prévision, Programme National Persée, vol. 190(4), pages 107-122.
    6. Malkamäki, Arttu & Toppinen, Anne & Kanninen, Markku, 2016. "Impacts of land use and land use changes on the resilience of beekeeping in Uruguay," Forest Policy and Economics, Elsevier, vol. 70(C), pages 113-123.
    7. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    8. Jeroen Bergh, 2007. "Evolutionary thinking in environmental economics," Journal of Evolutionary Economics, Springer, vol. 17(5), pages 521-549, October.
    9. Tesfatsion, Leigh, 2006. "Agent-Based Computational Modeling and Macroeconomics," ISU General Staff Papers 200601010800001585, Iowa State University, Department of Economics.
    10. Stefan Ambec & Alexis Garapin & Laurent Muller & Arnaud Reynaud & Carine Sebi, 2014. "Comparing Regulations to Protect the Commons: An Experimental Investigation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 58(2), pages 219-244, June.
    11. Feola, Giuseppe & Binder, Claudia R., 2010. "Towards an improved understanding of farmers' behaviour: The integrative agent-centred (IAC) framework," Ecological Economics, Elsevier, vol. 69(12), pages 2323-2333, October.
    12. repec:eee:ecomod:v:229:y:2012:i:c:p:25-36 is not listed on IDEAS
    13. Happe, Kathrin & Balmann, Alfons, 2008. "Doing Policy In The Lab! Options For The Future Use Of Model-Based Policy Analysis For Complex Decision-Making," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6588, European Association of Agricultural Economists.
    14. Welch, Eric W. & Shin, Eunjung & Long, Jennifer, 2013. "Potential effects of the Nagoya Protocol on the exchange of non-plant genetic resources for scientific research: Actors, paths, and consequences," Ecological Economics, Elsevier, vol. 86(C), pages 136-147.
    15. repec:eee:ecomod:v:222:y:2011:i:14:p:2213-2226 is not listed on IDEAS

    More about this item

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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