High-speed railway, factor flow and enterprise innovation efficiency: An empirical analysis on micro data

Xuehui Yang, Huirong Zhang and Yan Li

Socio-Economic Planning Sciences, 2022, vol. 82, issue PB

Abstract: Based on the data of listed companies at 285 cities prefecture level and above from 2003 to 2017, this paper empirically studies the impact of high-speed rail on enterprise innovation efficiency. By using the Difference-in-Difference (DID) method, empirical results indicate that high-speed railway can improve the innovation efficiency of listed companies. After parallel trend test of DID, the method of Propensity Score Matching and Difference-in-Difference (PSM-DID) and instrumental variable method and robustness test, the conclusion is still stable. The mediating mechanism of high-speed railway to improve enterprise innovation efficiency is to promote the flow of technical personnel and improve the knowledge spillover density of cities. Further heterogeneity analysis shows that high-speed railway has different impacts on innovation efficiency of different regions, administrative levels, cities with different population sizes, different industries and enterprises with different property rights. The policy suggestion is that we should pay attention to the positive role of high-speed rail in the formulation of enterprise innovation and development strategy.

Keywords: High-speed railway; Enterprise innovation efficiency; Heterogeneity; Factor flow (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0038012122000908
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:soceps:v:82:y:2022:i:pb:s0038012122000908

DOI: 10.1016/j.seps.2022.101305

Access Statistics for this article

Socio-Economic Planning Sciences is currently edited by Barnett R. Parker

More articles in Socio-Economic Planning Sciences from Elsevier
Bibliographic data for series maintained by Catherine Liu ().