Despite the People’s Republic of China government being the most aggressive in pursuing the carbon neutrality goal, it remains the world’s largest carbon emitter and polluting country. This study used 31 provinces’ panel data from 2010 to 2019 to compare fiscal decentralization’s impact on regional carbon emissions. It applied SBM-DEA undesirable models to calculate the Malmquist index and study environmental governance performance. It then used the systematic GMM model to explore fiscal decentralization’s influence on environmental governance performance. It is found that fiscal decentralization in eastern China exhibited a strong positive relationship with environmental governance performance. With high tax autonomy, local governments implemented the best tax policies for clean production, raising enthusiasm for enterprises’ green production. Nevertheless, there was no relationship between fiscal decentralization and environmental governance in poorer central and western regions with less tax collected. Benefits that arose from fiscal decentralization were limited. Moreover, more elite officials working in affluent cities and wealthier citizens have a higher expectation of environmental governance. These lead to better environmental and carbon emission policies. This paper also brings policy implications: 1) the central government should raise local government flexibility to use financial resources for environmental management. 2) Local government performance appraisal should include environmental protection (including carbon emission control). 3) The production taxes retained by local governments should be minimized to reduce governments’ incentives to obtain taxes from polluting/high energy consumption industries. 4) Raise government officials’ income in poorer regions to attract talented officials to work.
CITATION STYLE
Xia, J., Zhan, X., Li, R. Y. M., & Song, L. (2022). The Relationship Between Fiscal Decentralization and China’s Low Carbon Environmental Governance Performance: The Malmquist Index, an SBM-DEA and Systematic GMM Approaches. Frontiers in Environmental Science, 10. https://doi.org/10.3389/fenvs.2022.945922
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