Addressing uncertainty in decarbonisation policy mixes – Lessons learned from German and European bioenergy policy. (November 2017)

• Record Type: Journal Article
• Authors: Purkus, Alexandra; Gawel, Erik; Thrän, Daniela
• Is Part Of: Energy research & social science. Volume 33(2017)
• Page Start: 82
• Page End: 94
• Publication Date: 2017-11
• Subjects: Bioenergy policy -- Decarbonisation policy mixes -- Uncertainty -- New institutional economics; Power resources -- Social aspects -- Periodicals; Energy consumption -- Social aspects -- Periodicals; 333.7905
• DOI: 10.1016/j.erss.2017.09.020
• Languages: English
• ISSNs: 2214-6296

Abstract

Abstract: For promoting innovation in the context of sustainability transitions, research emphasizes the importance of combining technology-push and demand-pull instruments in a coordinated policy mix. Designing such policy mixes, however, remains challenging, due to path dependencies, interacting market failures, and uncertainty regarding eventual economic, environmental and societal impacts of innovations. This results in the need for a learning and flexible policy design, but simultaneously, stable political framework conditions are required to bring about lasting changes in production and consumption behaviour. This paper undertakes an economic assessment of how this trade-off between flexibility and stability has been addressed in practice, focussing on a case study of the European and German bioenergy policy mix which serves as a prime example for the challenges of dealing with uncertainty (e.g. regarding land use impacts, GHG balances, cost developments). Informed by the theory of second best, new institutional economics and the interdisciplinary policy mix literature, we identify dimensions for assessing whether relevant uncertainties, interactions between market failures and other constraints on first-best policy making have been handled in a rational manner. From the case study, we derive lessons for bioeconomy policy, as a further example of a decarbonisation policy mix faced by high uncertainty and complexity.