Booming with Speed: High-Speed Rail and Regional Green Innovation

Table 4

Mechanism test: labor flow and research capital flow.

Panel A: labor flow
	(1)	(2)	(3)	(4)	(5)
	NetL	GUMA	GIA	GUMG	GIG
L.HSR	0.140	0.137	0.159	0.128	0.0396
	(0.0425)	(0.0238)	(0.0295)	(0.0216)	(0.00667)
NetL		0.167	0.208	0.155	0.0493
		(0.0283)	(0.0377)	(0.0253)	(0.00916)
Controls	Yes	Yes	Yes	Yes	Yes
Year	Yes	Yes	Yes	Yes	Yes
City	Yes	Yes	Yes	Yes	Yes
N	3923	3923	3923	3923	3923
r2	0.0513	0.384	0.321	0.379	0.317
Panel B: research capital flow
	(1)	(2)	(3)	(4)	(5)
	NetC	GUMA	GIA	GUMG	GIG
L.HSR	0.261	0.156	0.182	0.144	0.0449
	(0.0666)	(0.0255)	(0.0313)	(0.0232)	(0.00763)
NetC		0.0163	0.0234	0.0204	0.00627
		(0.00880)	(0.0121)	(0.0107)	(0.00321)
Controls	Yes	Yes	Yes	Yes	Yes
Year	Yes	Yes	Yes	Yes	Yes
City	Yes	Yes	Yes	Yes	Yes
N	3923	3923	3923	3923	3923
r2	0.0471	0.325	0.261	0.317	0.252

Note: Panel A shows the result of labor flow as the mechanism, and Panel B shows the result of taking research capital flow as the mechanism. These two variables are constructed by the gravity model. Column (1) in both panels shows the result of the second step in the classic three-step model [85], and Columns (2–5) show the result of the third step (the result of the first step is shown in Columns (1–4) of Table 3). HSR and all control variables are included and lagged by one year in all regressions. All regressions include city fixed effects and year fixed effects. Robust standard errors in parentheses are clustered at the city level. The symbols , , and indicate significance at the 1%, 5%, and 10% levels, respectively.