Abstract
This paper aims at estimating the dynamic impact of renewable and non-renewable energy consumption, globalization, urbanization, and economic growth on the environmental quality. Unlike previous study, this study used multi-dimensional indicator of environmental quality that is ecological footprint. Given the importance of renewable energy, a sample of top renewable energy consuming countries has been selected for analysis spanning the period 1991–2016. The analysis is carried out in panel data framework that considers the issues of cross sectional dependence and heterogeneity. The results of cointegration test show the existence of long-run equilibrium relationship among the variables. The long-run elasticity of pooled mean group shows positive impact of economic growth and non-renewable energy consumption on ecological footprint while negative impact is observed in case of renewable energy consumption, globalization and urbanization. The sensitivity of long-run elasticity has been checked with the help of fully modified ordinary least square and dynamic ordinary least square. Based on empirical findings, some policy implication has also been provided.
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assumes government technology, policies, and social preferences continue to evolve in the recent past.
EKC predicts the presence of inverted U-shaped relationship between counry’s growth and environmental degradation. The economic growth generates a more pollution at initial stage but before reaching a threshold level of income; economy moves toward clean environment and people demand better environmental quality.
attractiveness Index of renewable energy country (www.ey.com)
also reveals asymptotic distribution for each seven statistic where for group mean test it is normal
have merits of providing normally distributed estimator.
the cointegrating vectors derived from the DOLS estimation are asymptotically efficients
\( {\Delta z}_{\mathrm{it}}={\delta}_i\ \left({z}_{i,t}-{x}_i\ {y}_{i,t-1}\right)+\sum \limits_{k-0}^{n-1}{\vartheta}_{i\mathrm{k}}\ {\Delta z}_{i,t-1}+\sum \limits_{k-0}^{m-1}{\alpha}_{\mathrm{ik}}\ {\Delta y}_{i,t-k}+{\rho}_i+{\mu}_{\mathrm{it}} \) here, Z indicates dependent variable EF and zi, t − xi yi, t − 1 is magnitude of deviation towards long run equilibrium from short run deviation; δi is adjustment speed; δi signifies short run coefficients; xi is long run coefficients; ρi is time invariant (unobserved) county specific effect; t = 2, 3…T is time period and i = 1, 2, 3…M is cross sectional unit.
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All three authors have contributed equally. MAA made the analysis part while SH compiled introduction and literature review, and the overall formatting of the paper has been done by TM. All authors have read and approved the manuscript.
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Ansari, M.A., Haider, S. & Masood, T. Do renewable energy and globalization enhance ecological footprint: an analysis of top renewable energy countries?. Environ Sci Pollut Res 28, 6719–6732 (2021). https://doi.org/10.1007/s11356-020-10786-0
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DOI: https://doi.org/10.1007/s11356-020-10786-0