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Evaluation of energy resilience and adaptation policies: An energy efficiency analysis

Abstract In modern developed economies, one of the primary objectives is to manage the transition from polluting to cleaner technologies as efficiently as possible. By now, in the current empirical literature, one can identify technological spillovers from environmental innovations as a major driver of this process. Specific energy policy aspects connected with industry behaviour have yet to be explored. The aim of this paper is to investigate energy efficiency via environmental innovation and the resulting degree of resilience and adaptation of both developed and developing countries. The work applies the non-parametric DEA (Data Envelopment Analysis) framework and Tobit analysis. For this scope, it is built a panel dataset made of some 5000 observations based on energy policy and sustainable development variables for 136 OECD and non-OECD countries. The results show that knowledge spillovers from environmental innovations reduce inefficiency and therefore strengthen the resilience of economies that decide and manage to invest adequately in the transition to more sustainable technologies. Besides, OECD countries improve their energy efficiency scores over time, whilst non-OECD countries do not. This implies that sustainable technologies transition is made more efficient by environmental innovation but the process is fostered by disposing of a resilient economic system – hence, vulnerability can affect the transition. These hypotheses lead to important economic, social and environmental implications for energy policy modelling.
- Kean University United States
- University of Greenwich United Kingdom
- University of Greenwich United Kingdom
- Wenzhou-Kean University China (People's Republic of)
- Università degli studi di Salerno Italy
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).74 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
