中国高耗能产品生产与区域PM2.5浓度的动态关联效应——基于省级尺度的分析
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金凤君, 林美含, 张晓平, 李润奎
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Dynamic correlation of energy-intensive industrial output and regional PM2.5 concentration in China from a provincial perspective
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JIN Fengjun, LIN Meihan, ZHANG Xiaoping, LI Runkui
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表7 能源密集型产业对省域PM2.5浓度长期影响的回归结果
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Tab. 7 Regression results of long-term impact on energy intensive industries on provincial PM2.5 concentration
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变量 | 模型A | 模型B | 模型C | 模型D | FE | SYS-GMM | FE | SYS-GMM | FE | SYS-GMM | FE | SYS-GMM | Ther | 0.111 | -0.214*** | | | | | | | Cem | | | -0.018 | -0.058*** | | | | | Ste | | | | | 0.089*** | 0.205*** | | | Coke | | | | | | | 0.177*** | 0.119*** | GRP | 0.171** | 0.136*** | 0.256*** | 0.217*** | 0.137** | -0.134*** | 0.174*** | 0.123*** | Indus | 0.290*** | 0.297*** | 0.301*** | 0.325*** | 0.270*** | 0.333*** | 0.313*** | 0.301*** | Urban | 0.129** | 0.176*** | 0.168*** | 0.146*** | 0.111** | 0.073*** | 0.089* | -0.012 | ER | 1.673** | 1.413* | 1.492** | 1.369** | 1.313** | 1.371** | 1.865*** | 1.230* | L1.PM | | 0.639*** | | 0.630*** | | 0.587*** | | 0.577*** | Con | 22.130*** | -5.014** | 21.064*** | -4.235*** | 24.227*** | -0.889 | 22.546*** | 3.734* | N | 558 | 527 | 558 | 527 | 558 | 527 | 504 | 476 | Sargan | | 28.438 (1.0000) | | 28.823 (1.0000) | | 29.150 (1.0000) | | 26.740 (1.0000) | AR(1) | | -3.701 (0.0002) | | -3.677 (0.0002) | | -3.727 (0.0002) | | -3.738 (0.0002) | AR(2) | | -0.750 (0.4530) | | -0.967 (0.3333) | | -0.924 (0.3553) | | -2.055 (0.0399) |
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