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首页> 外文期刊>Environmental Science and Pollution Research >Total retail goods consumption, industry structure, urban population growth and pollution intensity: an application of panel data analysis for China
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Total retail goods consumption, industry structure, urban population growth and pollution intensity: an application of panel data analysis for China

机译:零售商品总量消费,产业结构,城市人口增长和污染强度:中国面板数据分析适用于中国

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摘要

There has been a growing concern regarding the regulation of environmental pollution in the face of a growing population, global warming, and climate change. Governments around the world have devised various mechanisms and policy strategies to ameliorate the worsening condition of natural environment around the world. Similar to the developed world, in China, the government is also aware of deteriorating environmental conditions. Hence, the existing abatement instruments include pollution discharge fees and several other policy strategies. This research is conducted to investigate the association between pollution intensity and its determinants, i.e., pollutant discharge fees and urban population, third industry structure, and total retail goods consumption. The secondary data of 29 provinces is used for empirical analysis. The principal component analysis is used to develop a single index called pollution intensity, and panel autoregressive distributed lags model (ARDL), or pooled mean group (PMG) analysis, is employed to find long-run and short-run relationship. The empirical findings show that pollution discharge fees negatively affects pollution intensity. Total retail good consumption and urban population increase pollution intensity. However, third industry structure helps to control pollution intensity. These results suggest reforms in the existing environmental regulations policy by targeting more pollutant intensive provinces.
机译:面对不断增长的人口,全球变暖和气候变化,对环境污染的监管越来越令人担忧。世界各地政府制定了各种机制和政策战略,以改善世界各地自然环境的恶化条件。与发达国家类似,在中国,政府也意识到环境条件恶化。因此,现有的减排工具包括污染退出费用和其他几项政策策略。进行该研究探讨污染强度及其决定因素之间的关联,即污染物排放费用和城市人口,第三种行业结构以及零售商品消费。 29个省份的二级数据用于实证分析。主要成分分析用于开发一个名为污染强度的单个索引,并且面板自回归分布式滞后模型(ARDL)或汇集平均组(PMG)分析用于寻找长期和短路关系。经验研究结果表明,污染排放费用对污染强度产生负面影响。总零售良好消费和城市人口增加污染强度。然而,第三种行业结构有助于控制污染强度。这些结果通过针对更污染物密集的省份来说,提出了现有环境法规政策的改革。

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