Abstract
This study investigates the heterogeneous causal linkages between urbanization, the intensity of electric power consumption, water-based pollutant emissions, and GRP in regional China by developing an urbanization-augmented “Stochastic Impacts by Regression on Population, Affluence, and Technology” (STIRPAT) model. A whole country panel of 29 provinces as well as region sub-panels of China, for the period 1999 to 2018, are estimated employing common correlated effects mean group approach (CCEMGA), which offers robustness against heterogeneous characteristics and cross-sectionally dependent series. From the theoretic modeling aspect, the intensity of electric power consumption and urbanization have been introduced as the determinants of water-based pollutant emissions in the STIRPAT modeling framework. Based on empirical results, first, GRP growth has shown appealing behavior in the form of its heterogeneous impacts on water-based pollutant emissions growth in the case of different regions. For instance, its impact is noted to be positive and statistically significant for the western region, which turned positive but statistically insignificant for the intermediate region. And it further turned significantly negative in the case of the eastern region. We call this phenomenon as “development level-based emission mitigation effect.” Second, in terms of the impact of GRP growth on urbanization, the “development-based urbanization ladder effect” has been found. Based on heterogeneous causal links, firstly, the existence of a positive bilateral causal link between the intensity of electric power consumption and GRP growth and urbanization and GRP growth has been validated. Secondly, a positive unidirectional causal link emerged from urbanization to the intensity of electric power consumption and water-based pollutant emissions growth. Thirdly, the causal connection between GRP growth and water-based pollutant emissions growth remained very interesting and of mixed nature. Based on empirical findings, useful policies are extended.
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Abbreviations
- WPE:
-
Water-based pollutant emissions
- URN:
-
Urbanization
- EP:
-
Economic progress
- GRP:
-
Gross regional product
- GDP:
-
Gross domestic product
- Pop:
-
Population
- CPI:
-
Consumer price index
- CNY:
-
Chinese Yuan (currency unit)
- χ 2 :
-
Chi-square
- IEPC:
-
Intensity of electric power consumption
- Std. Dev.:
-
Standard deviation
- P :
-
Population size
- CCEMGA:
-
Common correlated effects mean group approach
- CV:
-
Coefficient of variation
- IPS:
-
Im-Pesaran-Shin
- CIPS:
-
Cross-section augmented IPS
- CD:
-
Cross-sectional dependence
- OLS:
-
Ordinary least square
- RMSE:
-
Root mean square error
- kWh:
-
Kilowatt-hour (electric power unit)
- A:
-
Affluence
- T:
-
Technology
- I:
-
Environmental effects
- STIRPAT:
-
Stochastic Impacts by Regression on Population, Affluence, and Technology
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Ahmad, M., Ahmed, N., Jabeen, M. et al. Empirics on heterogeneous links among urbanization, the intensity of electric power consumption, water-based emissions, and economic progress in regional China. Environ Sci Pollut Res 27, 38937–38950 (2020). https://doi.org/10.1007/s11356-020-09939-y
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DOI: https://doi.org/10.1007/s11356-020-09939-y