Abstract
This article examines for the first time the impact of disaggregated energy sources and institutional quality on the ecological footprint (EF) of 29 OECD countries, by explaining how the diversification in countries’ energy mix and their institutional performance are associated with sustainable environmental performance. We use panel data from 1984 to 2016 and we apply second-generation techniques to arrange the critical issues of cross-sectional dependence and heterogeneity. The applied cointegration tests expose a long-run equilibrium relationship that associates renewable/non-renewable energy consumption, economic growth, institutional quality, and the EF of OECD countries. The robust cross-sectional augmented distributed lag (CS-DL) estimator shows that economic growth and the adoption of non-renewable energies are detrimental to the environment, while the operational quality of institutions adds to ecological sustainability. Concurrently, the negative effect of renewables on EF does not seem to cause a significant beneficial impact on the environment. Moreover, there is evidence that non-renewable energy and institutional quality have a bidirectional causal association with EF. Also, a weak unidirectional causal effect is running from the EF to renewables consumption. The study further demonstrates the inefficient integration of renewable energy forms in OECD countries and the concomitant essential role of institutions on environmental sustainability by providing relevant policy orientations.
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Data availability
The dataset used during the current study are available from the corresponding author on reasonable request.
Notes
Mostly bioenergy, direct solar energy, geothermal energy, hydropower, ocean energy, and wind energy.
In the most optimistic scenarios, these shares of renewables will reach 43% in 2030 and almost 77% in 2050.
The 11 fastest developing economies: Bangladesh, Egypt, Indonesia, Iran, Korea, Mexico, Nigeria, Pakistan, Philippines, Turkey, and Vietnam.
Middle East and North Africa.
Brazil, Russia, India, China, and South Africa.
STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) is an extension of the IPAT (impact = population, affluence, technology) environmental accounting equation. It is a stochastic model that predicts non-proportional and non-monotonic functional relationships among the factors that are supposed to be related with the ecosystem’s performance.
Policy concentrated institutions that facilitate the policy implementation among different groups of interest, from regulators to environmental groups.
Institutions that are not strongly policy concentrated and influenced by a small number of interest groups in formulating policies.
Middle Eastern and African.
Organization of Islamic Cooperation.
Emerging Market and Developing Economies.
Electricity power from renewables such as wind, solar, geothermal, biomass, and water energy.
Electricity power from non-renewables such as coal, oil, and natural gas.
See Pesaran and Yamagata (2008) for detailed description.
e.g., LLC, Breitung, IPS, Fisher-ADF, Fisher PP
In this study, T=33.
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Both authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by TC who also written the first draft. CK guided the econometrics analysis and commented on previous versions of the manuscript. Both authors read and approved the final manuscript.
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Christoforidis, T., Katrakilidis, C. The dynamic role of institutional quality, renewable and non-renewable energy on the ecological footprint of OECD countries: do institutions and renewables function as leverage points for environmental sustainability?. Environ Sci Pollut Res 28, 53888–53907 (2021). https://doi.org/10.1007/s11356-021-13877-8
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DOI: https://doi.org/10.1007/s11356-021-13877-8