| Title |
Eco-innovations, green growth, and environmental taxes in EU countries: a panel quantile regression approach |
| ID_Doc |
31002 |
| Authors |
Khan, H; Dong, Y; Nuta, FM; Khan, I |
| Title |
Eco-innovations, green growth, and environmental taxes in EU countries: a panel quantile regression approach |
| Year |
2023 |
| Published |
Environmental Science And Pollution Research, 30, 49 |
| DOI |
10.1007/s11356-023-29957-w |
| Abstract |
The purpose of this study is to examine how environmental taxation, green growth, and eco-innovations contribute to a more sustainable environment. This study examines the influence of green growth, environmental taxes, and eco-innovations on carbon dioxide emissions in 26 environmentally responsive European Union (EU) countries from 2000 to 2020. The analysis was conducted using the second-generation panel unit root test, cross-sectional dependence, panel cointegration, and panel quantile regression. Theoretical and empirical research has demonstrated that both linear and non-linear green growth strategies are effective in reducing CO2 emissions. There is evidence that CO2 emissions can be reduced through the implementation of environmental taxes, eco-innovations, the use of renewable energy sources, and enhanced energy efficiency. In contrast, economic growth has a positive effect on carbon emissions, and its square term verifies the environmental Kuznets curve. Nevertheless, our research findings provide empirical support for the hypothesis that sustainable development contributes to the maintenance of stringent environmental standards. For the sampled countries, the study's findings have significant policy implications. These results encourage governments to prioritize green growth over traditional economic growth and to encourage eco-innovations in renewable energy technology. |
| Author Keywords |
Environmental taxes; Green growth; Eco-innovations; Renewable energy consumption; CO2 emission; EU countries |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001073523400012 |
| WoS Category |
Environmental Sciences |
| Research Area |
Environmental Sciences & Ecology |
| PDF |
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