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Does economic growth and energy consumption drive environmental degradation in China's 31 provinces? New evidence from a spatial econometric perspective

机译:经济增长和能源消耗是否会导致中国31个省的环境恶化?空间计量经济学的新证据

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摘要

The panel data analysis points to economic and social factors contributing to NOx, PM2.5, PM10, SO2, and VOCs in China's 31 provinces. The spatial correlation analysis using Global and Local Moran's I values indicates the existence of a significant and positive spatial autocorrelation with respect to environment, economy and energy, and the high spatial correlation is evident in the eastern region, covering the northern part of Yangtze River Delta, Huaihai Economic Zone, and the lower reaches of the Yellow River Economic Belt. The empirical estimation is performed through spatial lag and spatial Durbin models. All emitted air pollutants in 31 provinces have significant spatial dependence and strong spillover effects. There is an inverted U-shaped relationship between emitted air pollutants (NOx, PM10, VOCs, and PM2.5) and per capita GDP, which follows the EKC hypothesis. The relationship between SO2 and per capita GDP does not follow the EKC hypothesis. There is a positive relationship between pollutant emissions and coal consumption, which is consistent with current studies for various countries like Canada, Denmark, UK and US and regions like New York State. However, the effects of science and technology investment on air pollutants are mostly positive, which is not as policy expected.
机译:面板数据分析指出了影响中国31个省的NOx,PM2.5,PM10,SO2和VOC的经济和社会因素。使用全局和局部Moran的I值进行的空间相关性分析表明,在环境,经济和能源方面存在显着且正的空间自相关,并且在覆盖长江三角洲北部的东部地区存在明显的高空间相关性。 ,淮海经济区和黄河经济带的下游。通过空间滞后和空间杜宾模型进行经验估计。 31个省的所有排放的空气污染物具有显着的空间依赖性和强烈的溢出效应。遵循EKC假设,排放的空气污染物(NOx,PM10,VOC和PM2.5)与人均GDP之间存在倒U型关系。二氧化硫与人均GDP之间的关系不遵循EKC假设。污染物排放与煤炭消耗之间存在正相关关系,这与加拿大,丹麦,英国和美国等多个国家和纽约州等地区的最新研究一致。但是,科学技术投资对空气污染物的影响大多是积极的,这与政策预期的不同。

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