中国城市网络地位对碳排放效率的影响
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盛科荣, 李晓瑞, 孙威, 王传阳
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Examining the impacts of network position on urban carbon emissions efficiency in China
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SHENG Kerong, LI Xiaorui, SUN Wei, WANG Chuanyang
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表3 面板Tobit模型基准回归结果(n=1132)
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Tab. 3 The baseline regression results of panel Tobit model
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| (1) | (2) | (3) | (4) | (5) | (6) | | Degree | 0.0474***
(0.013) | 0.0378**
(0.015) | | | | | | Between | | | 0.0209***
(0.006) | 0.0166**
(0.007) | | | | Eigen | | | | | 0.0042***
(0.001) | 0.0039***
(0.001) | | Urban | | -0.1194***
(0.045) | | -0.1210***
(0.046) | | -0.1360***
(0.047) | | Indust | | 0.1900***
(0.052) | | 0.1886***
(0.052) | | 0.1928***
(0.052) | | Reasch | | 0.0031
(0.005) | | 0.0041
(0.005) | | 0.0023
(0.005) | | FDI | | 0.0049*
(0.003) | | 0.0050*
(0.003) | | 0.0048*
(0.003) | | Passe | | 0.0097**
(0.004) | | 0.0100***
(0.004) | | 0.0091**
(0.004) | | Gov | | -0.0025
(0.003) | | -0.0031
(0.003) | | -0.0032
(0.003) | | 个体效应 | 是 | 是 | 是 | 是 | 是 | 是 | | 时间效应 | 是 | 是 | 是 | 是 | 是 | 是 | | 常数项 | 0.4007***
(0.014) | 0.3388***
(0.053) | 0.4253***
(0.010) | 0.3531***
(0.054) | 0.4184***
(0.011) | 0.3651***
(0.055) | | Log likelihood | 762.93 | 776.43 | 761.58 | 775.94 | 762.74 | 777.22 | | LR test | 499.46***
(0.000) | 467.33***
(0.000) | 513.36***
(0.000) | 471.50***
(0.000) | 495.92***
(0.000) | 459.84***
(0.000) | | Wald chi2(10) | 112.64***
(0.000) | 142.56***
(0.000) | 110.08***
(0.000) | 141.71***
(0.000) | 112.13***
(0.000) | 144.13***
(0.000) |
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