基于PLS方法的高技术产业发展对工业污染影响效应测度与分析

Measurement and analysis of influence effect of high-tech industry development on industrial pollution based on PLS method

以安徽省为例,运用熵值赋权法对工业污染状况进行评价;基于STIRPAT模型,采用典型相关与偏最小二乘回归(PLS)分析方法,就高技术产业发展对工业污染影响效应进行考察。结果表明:工业污染指数由2005年的0.537 1降至2015年的0.469 3,年均下降1.34%;高技术产业发展、经济发展、固定资产投资、城镇化水平、人均居民消费水平、直接利用外资额、环境规制、产业结构、市场化程度均为工业污染驱动因子;高技术产业发展、经济发展、城镇化水平、人均居民消费水平、经济发展与高技术产业发展交互项对工业污染具有显著抑制作用,当其增加1%时,分别导致工业污染指数下降0.087 8%、0.047 0%、0.000 9%、0.027 6%、0.259 8%;固定资产投资、产业结构、直接利用外资额、市场化程度、环境规制对工业污染具有正向驱动作用,当其增加1%时,工业污染指数分别增加0.036 6%、0.000 2%、0.271 8%、0.008 1%、0.031 8%。

Taking Anhui Province as an example, the entropy weighting method was used to evaluate the industrial pollution situation. Based on STIRPAT model, the typical correlation and partial least squares regression analysis methods were adopted to investigate the influence effect of industrial pollution caused by high-tech industry. The results showed that firstly, the pollution index decreased from 0. 537 1 in 2005 to 0. 469 3 in 2015 with annual average reduction of 1. 34%. Secondly, the driving factors of industrial pollution include high-tech industry development, economic growth, fixed asset investments, urbanization, per capital household consumption level,direct foreign investment, environmental regulation policies, industrial structure and marketization degree. Thirdly,the high-tech industry development, economic growth, urbanization level, per capital household consumption level and the interaction terms of economic development and high-tech industry development make significant inhibitory effects on industrial pollution; with their increase rate of 1%, the industrial pollution index is caused to decrease by0. 087 8%, 0. 047 0%, 0. 000 9%, 0. 027 6% and 0. 259 8% respectively. Fourthly, the fixed asset investments, industrial structure, direct foreign investment, marketization degree and environmental regulation have positive driving effects on industrial pollution; when increasing by 1%, the industrial pollution index increases by0. 036 6%, 0. 000 2%, 0. 271 8%, 0. 008 1% and 0. 031 8% respectively.