Unknown

Dataset Information

0

Environmental pollution and economic growth: Evidence of SO2 emissions and GDP in China.


ABSTRACT: This study explores the inherent linkage mechanism between environmental pollution and economic growth using a non-linear MS (M)-VAR (p) model. The results indicate that, first, the growth rates of China's gross domestic product (GDP) and SO2 emissions are in a state of significant inertia. Second, when the system was in a medium-growth regime, the growth rates of SO2 emissions and GDP had a positive correlation, characterized by lower probability and weaker durability. Third, when the system was in a high- or low-growth regime, their growth rates were negatively correlated, characterized by higher probability and stronger durability. Overall, economic growth increases environmental pollution emissions, which intensifies as well as inhibits economic growth. The correlation and sustainability of SO2 emissions and GDP are closely related to the regional status of the entire system. This study is helpful in analyzing the reasons for the nonlinear linkage mechanism between environmental pollution and economic growth.

SUBMITTER: Yan C 

PROVIDER: S-EPMC9684716 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

altmetric image

Publications

Environmental pollution and economic growth: Evidence of SO<sub>2</sub> emissions and GDP in China.

Yan Chao C   Li Huixuan H   Li Zhigang Z  

Frontiers in public health 20221110


This study explores the inherent linkage mechanism between environmental pollution and economic growth using a non-linear MS (M)-VAR (p) model. The results indicate that, first, the growth rates of China's gross domestic product (GDP) and SO<sub>2</sub> emissions are in a state of significant inertia. Second, when the system was in a medium-growth regime, the growth rates of SO<sub>2</sub> emissions and GDP had a positive correlation, characterized by lower probability and weaker durability. Thi  ...[more]

Similar Datasets

| S-EPMC8458215 | biostudies-literature
| S-EPMC10679152 | biostudies-literature
| S-EPMC7918594 | biostudies-literature
| S-EPMC10289335 | biostudies-literature
| S-EPMC5065220 | biostudies-literature
| S-EPMC11336269 | biostudies-literature
| S-EPMC6532921 | biostudies-literature
| S-EPMC10833537 | biostudies-literature
| S-EPMC10817194 | biostudies-literature
| S-EPMC7443063 | biostudies-literature