Can high-speed train improve the innovation ability of enterprises?

Figures & data

Table 1. Differences in the number of patents between enterprises in areas where high-speed railways are built and those in areas where they are not built.

	No high-speed railway construction area		Construction of high-speed rail areas		(2)-(1)
	Number of Enterprises	Number of patents (1)	Number of Enterprises	Number of patents (2)
Total number of patents	2885	1.1473	9585	1.2808	0.1335*** (3.7494)
Number of Invention Patent Applications	2885	0.5887	2885	0.7060	0.1173*** (4.5694)
Patents granted	2885	0.4185	2885	0.4868	0.0683*** (3.3130)

*, ** and *** indicate significant at the 10%, 5% and 1% levels, respectively.

Table 2. Baseline regression results.

Variables	Total number of patents		Number of Invention Patent Applications		Number of Invention Patents Granted
High-speed rail construction	0.122**	0.115**	0.0656*	0.0552	0.0667**	0.0623**
	(2.089)	(1.962)	(1.693)	(1.391)	(2.218)	(2.016)
Enterprise size		0.112***		0.0417**		0.0334**
		(3.393)		(2.034)		(2.143)
Gearing ratio		0.216***		0.190***		0.0567
		(2.773)		(3.339)		(1.554)
(TobinQ)		−0.0192		−0.0225		−0.0230
		(−0.668)		(−1.262)		(−1.601)
Revenue level		−0.0122		−0.000560		−0.000306
		(−1.042)		(−0.0705)		(−0.0530)
Number of Management		0.0875		0.0997*		0.0950**
		(1.241)		(1.798)		(2.219)
Regional Human Capital Levels		0.0817		0.0762		0.0556
		(0.747)		(1.603)		(1.577)
Highway Passenger Volume		−0.0167*		−0.0247***		−0.00592
		(−1.867)		(−4.208)		(−1271)
Regional Economic Level		−0.0375		−0.0357		−0.0161
		(−0.872)		(−1.455)		(−0.920)
Constants	0.787**	−1.330*	0.358***	−0.425	0.259***	−0.663*
	(17.51)	(−1.711)	(11.83)	(−0.903)	(10.77)	(−1.900)
Enterprise fixed effects	YES	YES	YES	YES	YES	YES
Year fixed effect	YES	YES	YES	YES	YES	YES
Sample size	12,470	12,440	12,470	12,440	12,470	12,440
R^2	0.056	0.060	0.081	0.088	0.055	0.059

*, ** and *** indicate significant at the 10%, 5% and 1% levels, respectively.

Table 3. Propensity score matching results.

Control variables		Average value		Standardization	T-test
		Processing group	Control group	Deviation	T-value	P-value
Business Size	Before Matching	22.202	22.101	7.3	3.55	0.000
	After Match	22.197	22,191	0.5	0.31	0.754
Return on Assets	Before Match	0.40618	0.40154	2.5	1.23	0.217
	After Match	0.40455	0.40520	−0.3	−0.26	0.798
Enterprise Market Value	Before Match	1.0397	1.03	1.3	1.13	0.260
	After Match	1.0386	1.0427	−1.0	−0.65	0.514
Revenue Level	Before Match	21.536	21.423	6.3	3.18	0.001
	After Match	21.533	21.540	−0.4	−0.30	0.768
Number of Management	Before Match	2.002	2.068	−3.4	−1.67	0.096
	After Match	2.0038	2.0092	−1.2	−0.81	0.416

Table 4. PSM-DID results.

Variables	Total number of patents
High-speed rail construction	0.122**	0.115**
	(2.085)	(1.965)
Corporate fixed effects	YES	YES
Year fixed effects	YES	YES
Sample size	12,470	12,440
R^2	0.056	0.060

*, ** and *** indicate significant at the 10%, 5% and 1% levels, respectively.

Table 5. Placebo test.

Variables	Total number of patents
Pre-High Speed Rail Construction Phase 1	0.00971
	(0.198)
Pre-High Speed Rail Construction Phase 2		−0.00306
		(−0.00593)
First 3 periods of high-speed rail construction			−0.0102
			(−0.204)
Enterprise fixed effect	YES	YES	YES
Year fixed effect	YES	YES	YES
Sample size	12,460	12,460	12,460
R^2	0.059	0.059	0.059

*, ** and *** indicate significant at the 10%, 5% and 1% levels, respectively.

Table 6. Instrumental variables regression.

Variables	Total number of patents
HRL instrumental variable (IV)	0.719***
	(4.825)
Firm fixed effects	YES
Year fixed effects	YES
Sample size	12,440
R^2	0.053

*, ** and *** indicate significant at the 10%, 5% and 1% levels, respectively.

Table 7. Regression of human capital mediating effects.

Variables	Total number of patents	Percentage of R&D staff	Total number of patents
R&D staff share			0.038***
			(4.475)
High-speed rail construction	0.115**	0.222***	0.107*
	(1.932)	(3.131)	(1.828)
Enterprise fixed effects	YES	YES	YES
Year fixed effect	YES	YES	YES
Sample size	12,460	12,460	12,460
R^2	0.060	0.824	0.062

*, ** and *** indicate significant at the 10%, 5% and 1% levels, respectively.

Table 8. Regression of transportation distance on firm innovation.

Variables	OLS	LSDV	LSDV
Transportation distance	−0.00349**	−0.00321**	−0.00444***	−0.00414***
	(−2.355)	(−2.274)	(−3.061)	(−2.770)
High-speed rail*Traffic distance			0.00083***	0.008849***
			(3.370)	(3.413)
Enterprise fixed effects	YES	YES	YES	YES
Year fixed effect	YES	YES	YES	YES
Sample size	12,460	12,460	12,470	12,460
R^2	0.059	0.097	0.056	0.060

*, ** and *** indicate significant at the 10%, 5% and 1% levels, respectively.

Table 9. Intermediation effect of marketization level.

Variables	R&D expenses as a percentage	Marketability Level	R&D expenses as a percentage
Level of marketization			0.0704***
			(4.639)
High-speed rail construction	1.077**	0.624***	1.033**
	(2.252)	(11.29)	(2.146)
Corporate fixed effects	YES	YES	YES
Year fixed effect	YES	YES	YES
Sample size	12,460	12,460	12,460
R^2	0.306	0.176	0.306

Note: *, ** and *** indicate significant at the 10%, 5% and 1% levels, respectively.

Table 10. The impact of the level of marketization on the factors of the enterprise.

Variables	Current assets ratio	Return on Assets	Market Competition (HHI)
Level of marketization	0.0633*	0.0361***	−0.0414***
	(1.705)	(6.527)	(−36.40)
Firm fixed effects	YES	YES	YES
Year fixed effects	YES	YES	YES
Sample size	12,470	12,450	12,470
R^2	0.009	0.007	0.111

*, ** and *** indicate significant at the 10%, 5% and 1% levels, respectively.

Data availability statement

The submitted article appears all data, models, and code generated or used during the study.