Identifying the Impact of Industrial Agglomeration on China’s Carbon Emissions Based on the Spatial Econometric Analysis

Table 7

Robustness test results of the impact of SA and DA on carbon emissions.

Variable	Adjusting the period		Remeasuring the variable		Economic weight matrix
	(1)	(2)	(3)	(4)	(5)	(6)
L.lnCE	0.951	1.009	0.956	0.985	0.968	1.007
	(0.025)	(0.024)	(0.021)	(0.020)	(0.023)	(0.021)
W×L.lnCE	−0.296	−0.264	−0.174	−0.160	−0.264	−0.273
	(0.072)	(0.073)	(0.073)	(0.073)	(0.098)	(0.099)
W×lnCE	0.308	0.321	0.259	0.273	0.361	0.394
	(0.066)	(0.067)	(0.063)	(0.063)	(0.090)	(0.089)
lnSA	0.136		0.088		0.096
	(0.046)		(0.034)		(0.037)
lnDA		−0.016		−0.016		−0.021
		(0.009)		(0.007)		(0.007)
lnpgdp	−0.002	0.004	−0.058	−0.012	0.007	0.020
	(0.037)	(0.039)	(0.033)	(0.032)	(0.032)	(0.032)
lner	0.045	0.042	0.038	0.035	0.046	0.039
	(0.024)	(0.025)	(0.019)	(0.019)	(0.021)	(0.021)
[lner]^2	−0.004	−0.004	−0.005	−0.005	−0.006	−0.005
	(0.004)	(0.004)	(0.003)	(0.003)	(0.003)	(0.003)
ur	−0.311	−0.439	−0.077	−0.125	−0.426	−0.515
	(0.192)	(0.199)	(0.135)	(0.137)	(0.149)	(0.150)
lninf	−0.107	−0.124	−0.063	−0.071	−0.075	−0.086
	(0.029)	(0.030)	(0.021)	(0.021)	(0.023)	(0.023)
Log-likelihood	777.076	764.061	917.570	909.683	875.792	867.675
Obs	450	450	510	510	510	510

Standard errors are reported in parentheses. , , and represent significance at 1%, 5%, and 10% levels, respectively.