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

Table 9

Results of analysis of heterogeneity in the impact of the digital economy on urban innovation.

Variable	Eastern	Middle-western	Southern	Northern
	(1)	(2)	(3)	(4)
DE	0.394	0.874∗∗∗	1.162∗∗∗	1.605∗∗
	(1.29)	(3.74)	(4.69)	(2.12)
Wx_DE	−0.497	0.747∗	−0.138	1.383∗∗∗
	(−0.78)	(1.73)	(−0.27)	(2.66)
Rho	0.512∗∗∗	0.633∗∗∗	0.641∗∗∗	0.627∗∗∗
	(11.54)	(21.43)	(17.49)	(18.82)
DE-direct effect	0.375	1.013∗∗∗	1.219∗∗∗	1.812∗∗∗
	(1.22)	(4.32)	(4.89)	(2.82)
DE-indirect effect	−0.452	3.478∗∗∗	1.746	4.602∗∗∗
	(−0.33)	(3.06)	(1.18)	(3.42)
DE-total effect	−0.077	4.490∗∗∗	2.965∗	6.414∗∗∗
	(−0.05)	(3.80)	(1.94)	(3.83)
Control variable	Yes	Yes	Yes	Yes
Individual-FE	Yes	Yes	Yes	Yes
Year-FE	Yes	Yes	Yes	Yes
Adj. R-sq	918	2115	1620	1413
N	0.7910	0.7002	0.7698	0.6661

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