| Abstrakt: |
An improved level of urbanization may slow the problem of environmental degradation and achieve green economic development. This study examined the use of the panel vector autoregressive (PVAR) model in discussing the relationship between economic growth, urbanization, energy consumption, and carbon emissions based on annual data from 30 Chinese provinces (municipalities and autonomous regions) for the period of 2000–2019. Meanwhile, the short- and long-term dynamics of urbanization, economic growth, and carbon emissions are better captured by using impulse response function tools. The PVAR model is able to perfectly solve the problem of endogeneity between variables, which has been mostly ignored in the energy environment literature. The results of the study are as follows. First, urbanization has the strongest impact on carbon emissions in the eastern region and a weaker impact on other regions. The impact of economic growth on environmental quality lessens gradually from the western and north-eastern regions to the central region and then the eastern region, with a clear regional gradient. Second, the causal relationships between urbanization and carbon emissions and between energy consumption and carbon emissions are unidirectional and significant only in the eastern region. All four regions have a unidirectional causal relationship between economic growth and carbon emissions. Unidirectional causality between urbanization and economic growth exists in the eastern, western, and north-eastern regions. Third, the impulse response results show that urbanization has more short-term than long-term effects on carbon emissions in the eastern region, both long- and short-term effects in the west and north-east, and only short-term effects in the central region. Economic growth and energy consumption in the central and north-eastern regions improve environmental quality in the short term until the third lag period, which shows the beginning of deteriorating environmental quality. [ABSTRACT FROM AUTHOR] |
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