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Foxes, hedgehogs, and greenhouse governance: Knowledge, uncertainty, and international policy-making in a warming World

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  • Michel, David

Abstract

Global environmental challenges like greenhouse warming are characterized by profound uncertainties about the workings of complex systems, high stakes as to the costs and benefits of various possible actions, and important differences concerning the values that should shape public choices, confounding ready resolution by conventional decision-making procedures. So-called adaptive or reflexive governance strategies provide policy-makers an alternative framework for tackling the greenhouse problem. Adaptive governance employs deliberate experimentation and continuous learning-by-doing to test and adjust ongoing policy responses. Yet pursuing such approaches poses particular challenges to global climate cooperation. In an increasingly interdependent world, coordinating multiple parties experimentally adopting different climate measures could prove contentious. Unequivocal policy lessons may be difficult to draw and apply. Timely collective revisions to ongoing policies may prove more difficult still to define and agree. Advocates must engage these issues directly and develop means of addressing them if adaptive governance approaches are to allow policy-makers to formulate better strategies for combating climate change.

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  • Michel, David, 2009. "Foxes, hedgehogs, and greenhouse governance: Knowledge, uncertainty, and international policy-making in a warming World," Applied Energy, Elsevier, vol. 86(2), pages 258-264, February.
  • Handle: RePEc:eee:appene:v:86:y:2009:i:2:p:258-264
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    2. Elinor Ostrom, 2016. "Nested Externalities and Polycentric Institutions: Must We Wait for Global Solutions to Climate Change Before Taking Actions at Other Scales?," Studies in Economic Theory, in: Graciela Chichilnisky & Armon Rezai (ed.), The Economics of the Global Environment, pages 259-276, Springer.
    3. Maria Cerretta & Lidia Diappi, 2014. "Adaptive Evaluations in Complex Contexts: Introduction," SCIENZE REGIONALI, FrancoAngeli Editore, vol. 2014(1 Suppl.), pages 5-22.
    4. Li, Y.P. & Huang, G.H. & Li, M.W., 2014. "An integrated optimization modeling approach for planning emission trading and clean-energy development under uncertainty," Renewable Energy, Elsevier, vol. 62(C), pages 31-46.
    5. Maria Cerreta & Eleonora Giovene di Girasole & Giuliano Poli & Stefania Regalbuto, 2020. "Operationalizing the Circular City Model for Naples’ City-Port: A Hybrid Development Strategy," Sustainability, MDPI, vol. 12(7), pages 1-26, April.
    6. Simoes, Sofia & Fortes, Patrícia & Seixas, Júlia & Huppes, Gjalt, 2015. "Assessing effects of exogenous assumptions in GHG emissions forecasts – a 2020 scenario study for Portugal using the Times energy technology model," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 221-235.
    7. Elinor Ostrom, 2014. "A Polycentric Approach For Coping With Climate Change," Annals of Economics and Finance, Society for AEF, vol. 15(1), pages 97-134, May.
    8. Wonglimpiyarat, Jarunee, 2010. "Technological change of the energy innovation system: From oil-based to bio-based energy," Applied Energy, Elsevier, vol. 87(3), pages 749-755, March.

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