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Creative Learning and Policy Ideas: The Global Rise of Green Growth

Published online by Cambridge University Press:  12 April 2021

Bentley B. Allan Open the ORCID record for Bentley B. Allan [Opens in a new window]  and
Jonas O. Meckling Open the ORCID record for Jonas O. Meckling [Opens in a new window]
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Abstract

Ideas play an important role in policy change. Theories of policy change, including rational and bounded learning, bracket what needs to be explained: the creation of new ideas. We develop a theory of creative learning in international organizations (IOs). It posits that IO officials respond to new problems and state practices by creating novel concepts and policy ideas. New ideas help officials to manage multiple pressures in their organization’s strategic situation. They enable officials to mediate principal demands while seeking to mobilize client states. We theorize three modes of creative learning that generate new ideas: conceptual combination, translation, and repurposing. Empirically, we explain a major change in global environmental policy: the rise of green growth ideas among major IOs, including the OECD, the UN, and the World Bank. Green growth ideas include new arguments drawn from Keynesian and Schumpeterian economics, which claim that environmental policies can drive economic growth. We show how these ideas were a creative response to the problem of climate change and emerging state interventions in support of clean energy. Our theory of creative learning applies beyond IOs to domestic politics and takes on added significance in times of transformative change that challenge the scripts of policymaking.

Type
Environmental Politics
Information
Perspectives on Politics , Volume 21 , Issue 2: Special Section: Green Political Science , June 2023 , pp. 443 - 461
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the American Political Science Association

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Footnotes

A list of permanent links to Supplemental Materials provided by the authors precedes the References section.

Data replication sets are available in Harvard Dataverse at: https://doi.org/10.7910/DVN/AE0MKQ

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