ecological footprint
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2022 ◽  
Vol 9 ◽  
Xiaowen Wan ◽  
Atif Jahanger ◽  
Muhammad Usman ◽  
Magdalena Radulescu ◽  
Daniel Balsalobre-Lorente ◽  

The study explores the association between economic complexity, globalization, renewable and non-renewable energy consumption on the ecological footprint in the case of India from 1990–2018. The autoregressive distributed lag (ARDL) is applied to measure the long-run elasticity, while the vector error correction model (VECM) is applied to classify the causal path. The empirical findings demonstrate that economic complexity, globalization process, and renewable energy consumption play a dominant role in minimizing environmental degradation. In contrast, economic growth and non-renewable energy consumption are more responsible for increasing the pollution level in both the short and long run. Furthermore, the VECM outcomes disclose that there is long-run causality between ecological footprint and economic complexity. Moreover, the empirical outcomes are robust to various robustness checks performed for analysis to the consistency of our main results. The Indian government/policymakers should encourage a more environmentally friendly production process and eco-friendly technologies in exports to minimize environmental degradation.

Menna Sherif ◽  
Dalia M. Ibrahiem ◽  
Khadiga M. El-Aasar

AbstractThis paper seeks to explore the potential function of technological innovation and clean power in mitigating the ecological footprint in the N-11 nations during the phase 1992–2015 by applying panel cointegration analysis. The outcomes of the panel cointegration test signify the occurrence of a long-run relation among the clean energy (CE) variable, the ecological footprint (EF) variable, the per capita GDP (Y) variable, the financial development (FIN) variable, and technological innovation (TI) variable. The outcomes of the VECM signify a long-run causal relation from the ecological footprint (EF) variable to the clean energy (CE) variable, the GDP per capita (Y) variable, and technological innovation (TI) variable. This implies that the environmental degradation faced by the N-11 countries leads to shifting toward clean energy sources and technological innovation in the long run. Thus, the N-11 countries are in need to design policies that enhance shifting toward environmentally friendly energy sources.

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