Abstract
In today’s world, where urbanization is at its pinnacle, has created a significant economic gap between rural and urban populations in developing economies and substantially influenced environmental degradation. This study investigates the relationship between urbanization and environmental degradation via carbon emissions among developing countries along the Belt and Road route from 1990 to 2019 while using economic production, energy consumption, and trade openness as control variables. The study engages current econometric methodologies to uncover accurate and reliable findings, and the outcomes reveal that the panel under investigation is cross-sectionally dependent and heterogeneous. Therefore, the AMG, CCEMG, and DCCEMG estimators are employed to examine the effect connection between the variables. The outcomes unveil that urbanization, economic production, and energy consumption escalate environmental degradation, but trade openness is confirmed as a trivial determinant of environmental degradation. Furthermore, the causal connections between the variables disclose bi-directional causalities between urbanization and environmental degradation and between energy consumption and environmental degradation. Nevertheless, uni-directional causalities are affirmed, spanning from economic production to environmental degradation and from trade openness to environmental degradation. Finally, policy implications are discussed.
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Data availability
The datasets used and/or analyzed during the current study will be made available on reasonable request.
Abbreviations
- URB:
-
urbanization
- EC:
-
energy consumption
- EP:
-
economic production
- TO:
-
trade openness
- CO2 :
-
carbon dioxide
- EF:
-
ecological footprint
- BRI:
-
Belt and Road Initiative
- DCCEMG:
-
dynamic common correlated effects mean group
- CCEMG:
-
common correlated effects mean group
- AMG:
-
augmented mean group
- WDI:
-
World Development Indicators
- CD:
-
cross-sectional dependence
- LM:
-
Lagrangian multiplier
- EKC:
-
environmental Kuznets curve
- ARDL:
-
autoregressive distributed lag
- FMOLS:
-
fully modified ordinary least squares
- DOLS:
-
dynamic ordinary least squares
- PSM-DID:
-
difference-in-difference analysis based on the propensity score matching method
- 2SLS:
-
2-stages least square
- GMM:
-
generalized method of moments
- DKSEM:
-
Driscoll-Kraay panel regression
- DSUR:
-
dynamic seemingly unrelated regression
- PQM:
-
panel quantile model
- PRM:
-
panel regression model
- NSR:
-
non-linear stochastic regression
- STIRPAT:
-
stochastic impacts regression on population, affluence, and technology
- VECM:
-
vector error correction model
- CADF:
-
cross-sectionally augmented Dickey-Fuller
- CIPS:
-
cross-sectional Im, Pesaran, and Shin
- VIF:
-
variance inflation factor
- D-H:
-
Dumitrescu and Hurlin
- H0 :
-
null hypothesis
- H1 :
-
alternative hypothesis
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Ahakwa, I. The role of economic production, energy consumption, and trade openness in urbanization-environment nexus: a heterogeneous analysis on developing economies along the Belt and Road route. Environ Sci Pollut Res 30, 49798–49816 (2023). https://doi.org/10.1007/s11356-023-25597-2
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DOI: https://doi.org/10.1007/s11356-023-25597-2