Digital Economy’s Spatial Implications on Urban Innovation and Its Threshold: Evidence from China

Table 8

Results of analysis of mechanisms of the digital economy to influence urban innovation.

Variable	lnUI	lnHR	lnTS	lnUI	lnUI	lnUI	lnUI
	(1)	(2)	(3)	(4)	(5)	(6)	(7)
DE	0.961∗∗∗	0.462∗∗∗	2.619∗∗∗			0.908∗∗∗	0.648∗∗∗
	(5.19)	(4.54)	(7.95)			(4.89)	(3.51)
lnHR				0.152∗∗∗		0.133∗∗∗	0.148∗∗∗
				(4.60)		(4.02)	(4.55)
lnTS					0.089∗∗∗		0.088∗∗∗
					(8.82)		(8.62)
Wx_DE	0.671∗	0.470∗∗	−0.906			0.652∗	0.317
	(1.78)	(2.29)	(−1.35)			(1.71)	(0.83)
Wx_lnHR				−0.029		−0.106	−0.144∗
				(−0.35)		(−1.26)	(−1.73)
Wx_lnTS					0.101∗∗∗		0.086∗∗∗
					(4.34)		(3.63)
Rho	0.696∗∗∗	0.348∗∗∗	0.557∗∗∗	0.720∗∗∗	0.668∗∗∗	0.697∗∗∗	0.657∗∗∗
	(27.64)	(10.19)	(19.03)	(29.90)	(26.05)	(27.75)	(25.02)
DE-direct effect	1.095∗∗∗	0.486∗∗∗	2.660∗∗∗			1.036∗∗∗	0.711∗∗∗
	(5.90)	(4.84)	(8.16)			(5.51)	(3.83)
lnHR-direct effect				0.161∗∗∗		0.128∗∗∗	0.142∗∗∗
				(4.75)		(4.31)	(5.21)
lnTS-direct effect					0.104∗∗∗		0.101∗∗∗
					(10.34)		(9.31)
DE-indirect effect	4.368∗∗∗	0.963∗∗∗	1.284			4.136∗∗∗	2.013∗∗
	(3.53)	(2.96)	(0.85)			(3.27)	(2.13)
lnHR-indirect effect				0.299		−0.067	−0.101
				(0.94)		(−0.28)	(−0.47)
lnTS-indirect effect					0.478∗∗∗		0.408∗∗∗
					(6.57)		(6.05)
DE-total effect	5.463∗∗∗	1.449∗∗∗	3.944∗∗			5.171∗∗∗	2.725∗∗∗
	(4.30)	(4.50)	(2.56)			(3.97)	(2.78)
lnHR-total effect				0.460		0.060	0.041
				(1.41)		(0.24)	(0.19)
lnTS-total effect					0.582∗∗∗		0.509∗∗∗
					(7.83)		(7.24)
Control variable	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Individual-FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Year-FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Adj. R-sq	0.7102	0.3798	0.4221	0.7029	0.7245	0.7112	0.7296
N	3033	3033	3033	3033	3033	3033	3033

Note. ∗∗∗, ∗∗, and ∗ represent the significance level at the 1%, 5%, and 10% levels, respectively. The numbers in brackets are the test values t.