Socioeconomic Drivers of Environmental Pollution in China: A Spatial Econometric Analysis
This paper studies the environmental pollution and its impacts in China using prefecture-level cities and municipalities data. Moran’s I, the widely used spatial autocorrelation index, provides a fairly strong pattern of spatial clustering of environmental pollution and suggests a fairly high stabil...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2017/4673262 |
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| _version_ | 1850222270818025472 |
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| author | Jianmin Liu Xia Chen Runchu Wei |
| author_facet | Jianmin Liu Xia Chen Runchu Wei |
| author_sort | Jianmin Liu |
| collection | DOAJ |
| description | This paper studies the environmental pollution and its impacts in China using prefecture-level cities and municipalities data. Moran’s I, the widely used spatial autocorrelation index, provides a fairly strong pattern of spatial clustering of environmental pollution and suggests a fairly high stability of the positive spatial correlation. To investigate the driving forces of environmental pollution and explore the relationship between fiscal decentralization, economic growth, and environmental pollution, spatial Durbin model is used for this analysis. The result shows that fiscal decentralization of local unit plays a significant role in promoting the environmental pollution and the feedback effect of fiscal decentralization on environmental pollution is also positive, though it is not significant. The relationship of GDP per capita and environmental pollution shows inverted U-shaped curve. Due to the scale effect of secondary industry, the higher the level of secondary industry development in a unit is, the easier it is to attract the secondary industry in adjacent units, which mitigates the environmental pollution in adjacent units. Densely populated areas tend to deteriorate local environment, but environmental regulation in densely populated areas is often tighter than other areas, which reduces environmental pollution to a certain extent. |
| format | Article |
| id | doaj-art-72695f546d6f4706a52d9c2823da2cd2 |
| institution | OA Journals |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-72695f546d6f4706a52d9c2823da2cd22025-08-20T02:06:23ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2017-01-01201710.1155/2017/46732624673262Socioeconomic Drivers of Environmental Pollution in China: A Spatial Econometric AnalysisJianmin Liu0Xia Chen1Runchu Wei2School of Economics & Trade, Hunan University, Changsha, Hunan Province 410079, ChinaSchool of Economics & Trade, Hunan University, Changsha, Hunan Province 410079, ChinaSchool of Hydraulic Engineering, Changsha University of Science and Technology, Changsha, Hunan Province 410114, ChinaThis paper studies the environmental pollution and its impacts in China using prefecture-level cities and municipalities data. Moran’s I, the widely used spatial autocorrelation index, provides a fairly strong pattern of spatial clustering of environmental pollution and suggests a fairly high stability of the positive spatial correlation. To investigate the driving forces of environmental pollution and explore the relationship between fiscal decentralization, economic growth, and environmental pollution, spatial Durbin model is used for this analysis. The result shows that fiscal decentralization of local unit plays a significant role in promoting the environmental pollution and the feedback effect of fiscal decentralization on environmental pollution is also positive, though it is not significant. The relationship of GDP per capita and environmental pollution shows inverted U-shaped curve. Due to the scale effect of secondary industry, the higher the level of secondary industry development in a unit is, the easier it is to attract the secondary industry in adjacent units, which mitigates the environmental pollution in adjacent units. Densely populated areas tend to deteriorate local environment, but environmental regulation in densely populated areas is often tighter than other areas, which reduces environmental pollution to a certain extent.http://dx.doi.org/10.1155/2017/4673262 |
| spellingShingle | Jianmin Liu Xia Chen Runchu Wei Socioeconomic Drivers of Environmental Pollution in China: A Spatial Econometric Analysis Discrete Dynamics in Nature and Society |
| title | Socioeconomic Drivers of Environmental Pollution in China: A Spatial Econometric Analysis |
| title_full | Socioeconomic Drivers of Environmental Pollution in China: A Spatial Econometric Analysis |
| title_fullStr | Socioeconomic Drivers of Environmental Pollution in China: A Spatial Econometric Analysis |
| title_full_unstemmed | Socioeconomic Drivers of Environmental Pollution in China: A Spatial Econometric Analysis |
| title_short | Socioeconomic Drivers of Environmental Pollution in China: A Spatial Econometric Analysis |
| title_sort | socioeconomic drivers of environmental pollution in china a spatial econometric analysis |
| url | http://dx.doi.org/10.1155/2017/4673262 |
| work_keys_str_mv | AT jianminliu socioeconomicdriversofenvironmentalpollutioninchinaaspatialeconometricanalysis AT xiachen socioeconomicdriversofenvironmentalpollutioninchinaaspatialeconometricanalysis AT runchuwei socioeconomicdriversofenvironmentalpollutioninchinaaspatialeconometricanalysis |