中国东部地区工业废水排放影响因素分析——基于STIRPAT框架与EKC假说

doi:10.13776/j.cnki.resourcesindustries.20221030.001

摘要/Abstract

摘要：

中国改革开放40年，在经济快速增长的同时也产生了一些较为严重的环境污染问题，其中废水作为“三废”之一就对我国的生态文明建设造成了巨大的污染治理压力。本文选取2003—2015年中国东部地区100座城市的年度面板数据，运用带有不同平滑变量的双向固定效应半参变系数模型，基于STIRPAT模型框架，对我国东部地区工业废水排放量与人均GDP、地方财政科学事业费支出、限额以上工业企业数量之间的内在联系展开研究。研究结果表明：1）经济增长与工业废水排放量之间存在正U型关系，当人均GDP的对数值为2.290 4时，人均GDP对工业废水排放的边际影响为-0.397 0，达到了U型曲线的最低点。2）第二产业在产业结构中所占比例对工业废水排放量的边际影响会随着地方财政科学事业费支出的增加显现出非线性，呈U型状态，即先下降后上升的发展趋势。人口密度对工业废水排放量的边际影响会随着限额以上工业企业数量的增加也显现出非线性，呈波动上升的U型状态，即先下降后小幅波动上升的发展趋势。3）当地方财政科学事业费支出的对数值为7.648 6时，第二产业占比对工业废水排放的边际影响为0.683 3；限额以上工业企业数量的对数值为5.315 5时，人口密度对工业废水排放的边际影响为-0.061 9，2个边际影响值均为曲线的最低点。研究结论：1）经济增长和地方财政科学事业费支出对工业废水排放均具有促进作用；限额以上工业企业数量对于工业废水排放具有先抑制后促进的作用，其边际影响均值前期为负，但随着限额以上工业企业数量的增加会呈现出由负变正的增大趋势。2）地方财政科学事业费支出每增加1%，将会通过第二产业占比促使工业废水排放量增加大约0.72%；限额以上工业企业数量每增加1%，前期将会通过人口密度促使工业废水排放量降低大约0.013%，但后期会随着限额以上工业企业数量的增加，同样通过人口密度促使工业废水排放量逐渐增加。

关键词: 工业废水排放, 双向固定效应, 半参变系数模型, STIRPAT, EKC

Abstract:

China’s rapid economic growth leads to environmental pollution since its openness 4 decades ago, of which waste water becomes a pressure on China’s ecological civilization. This paper, based on China’s 100 eastern cities’annual panel data, uses two-way fixed effects semiparametric variable coefficient model with different smooth variables and STIRPAT model to study the connection between industrial waste water discharge and GDP per capita, expenditure on local financial science undertakings, and number of industrial enterprises above designated size in eastern China. Economic growth has a positive U-shaped relation with industrial waste water discharge. The marginal impacting indicator of GDP per capita on industrial waste water discharge is -0.397 0 when the logarithm value of GDP per capita is 2.290 4, reaching the lowest point of the U-curve. The marginal impacting of the proportion of the secondary industry displays a non-linear U-shaped relation on industrial waste water discharge with expenditure on local financial science undertakings rises, first down and up. The marginal impacting of population density on industrial waste water discharge also shows a non-linear fluctuated rising U-shaped trend, first falling and then slightly rising with number of industrial enterprises above designated size are increasing. The marginal impacting indicator of the secondary industrial proportion on industrial waste water discharge is 0.683 3 when the logarithm value of expenditure on local financial science undertakings is 7.648 6. When the logarithm value of number of industrial enterprises above designated size is 5.315 5, the marginal impacting indicator of population density on industrial waste water discharge is -0.061 9, and both marginal impact values are the lowest points of the curve. It concludes that economic growth and expenditure on local financial science undertakings promote the industrial waste water discharge, the number of industrial enterprises above the designated size has the effect of inhibiting industrial waste water discharge first and then promoting it. The mean value of marginal impact is negative in the early stage, but with the increase of the number of industrial enterprises above the designated size, there will be an increasing trend from negative to positive. When the expenditure on local financial science undertakings increases by 1%, industrial waste water discharge will increase by 0.72% through the proportion of the secondary industry. When the number of industrial enterprises above the designated size increases by 1%, the industrial waste water discharge will decrease by about 0 013% in the early stage through the population density, but in the later stage, with the increase of the number of industrial enterprises above the designated size, the industrial waste water discharge will also increase gradually through the population density.

Key words:

industrial waste water discharge, two-way fixed effects, 〖JP2〗semiparametric coefficient model, STIRPAT, EKC

中图分类号:

X703
F427

贾顺顺. 中国东部地区工业废水排放影响因素分析——基于STIRPAT框架与EKC假说[J]. 资源与产业, 2022, 24(6): 116-126.

JIA Shunshun.

ANALYSIS ON INFLUENCING FACTORS OF INDUSTRIAL WASTE WATER DISCHARGE IN EASTERN CHINA：BASED ON STIRPAT FRAMEWORK AND EKC HYPOTHESIS [J]. Resources & Industries, 2022, 24(6): 116-126.

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[6]	高新伟, 朱源. 科研投入抑制碳排放了吗？——基于LMDI模型和STIRPAT模型的碳排放影响因素分析[J]. 资源与产业, 2020, 22(6): 37-45.
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[11]	查奇芬，成鑫. . 技术进步对中国区域碳排放的影响研究[J]. 资源与产业, 2017, 19(6): 71-77.
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