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Empirical study on the environmental Kuznets curve for CO2 in France: The role of nuclear energy

This paper attempts to estimate the environmental Kuznets curve (EKC) in the case of France by taking the role of nuclear energy in electricity production into account. We adopt the autoregressive distributed lag (ARDL) approach to cointegration as the estimation method. Additionally, we examine the stability of the estimated models and investigate the Granger causality relationships between the variables in the system. The results from our estimation provide evidence supporting the EKC hypothesis, and the estimated models are shown to be stable over the sample period. The uni-direction running from other variables to CO2 emissions are confirmed from the casualty tests. Specifically, the uni-directional causality relationship running from nuclear energy to CO2 emissions statistically provides evidence on the important role of nuclear energy in reducing CO2 emissions.
- Japan Society for the Promotion of Science United Kingdom
- Japan Society for the Promotion of Science United Kingdom
- Japan Society for the Promotion of Science Japan
- Kyoto University Japan
CO2; Environment; EKC; Nuclear; France; ARDL, jel: jel:Q51, jel: jel:Q43, jel: jel:Q53
CO2; Environment; EKC; Nuclear; France; ARDL, jel: jel:Q51, jel: jel:Q43, jel: jel:Q53
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).346 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 0.1% 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 1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
