Economic policy making for environmental problems as an interactive learning process
Martin de Wit
Abstract
Open-access reader
Martin de Wit
Abstract
Open-access reader
The foremost limitation of public policy approaches is that the context of the public policy problem is not taken into account. In the case of complex and dynamic environmental problems, such as global climate change, there is a need for a framework for approaching economic policy that takes account of the complexity and changing realities of such problems. The objective of this paper is to present a framework to approach economic policy making in a case of such complex and dynamic environmental problems. The literature on economic and public policy theories, the need for a systematic policy design process and approaches to complexity and dynamics in policy making is framework available to one where the focus is on the best learning process to facilitate economic policy making on complex and dynamic environmental problems. Based on sociological models of experiential learning, a multiple-loop learning framework (MLLF) is presented. This model illustrates the importance of orchestrated science-policy interactions through interactive learning. The opportunities and limitations of this model are discussed with reference to the debate on economic policy for global climate change.
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The foremost limitation of public policy approaches is that the context of the public policy problem is not taken into account. In the case of complex and dynamic environmental problems, such as global climate change, there is a need for a framework for approaching economic policy that takes account of the complexity and changing realities of such problems. The objective of this paper is to present a framework to approach economic policy making in a case of such complex and dynamic environmental problems. The literature on economic and public policy theories, the need for a systematic policy design process and approaches to complexity and dynamics in policy making is framework available to one where the focus is on the best learning process to facilitate economic policy making on complex and dynamic environmental problems. Based on sociological models of experiential learning, a multiple-loop learning framework (MLLF) is presented. This model illustrates the importance of orchestrated science-policy interactions through interactive learning. The opportunities and limitations of this model are discussed with reference to the debate on economic policy for global climate change.
Key concepts: Process (computing), Context (archaeology), Management science, Policy analysis, Public policy, Policy studies, Experiential learning, Economics