Connect to green: High-speed rail network and firms’ environmental performance

Abstract

High-speed rail (HSR) has completely revolutionized intercity travel, significantly impacting economic activities. Recent studies have increasingly focused on how HSR affects environmental pollution. Given China’s extensive HSR policy in recent years, we extend this discussion in the context of China, introducing several new dimensions. Firstly, by manually collecting the daily operating routes of each HSR line in China, we construct a dynamic, directed, and weighted HSR network and provide a detailed description of the topological evolution of Chinese HSR from 2007 to 2014. Secondly, by employing network theory algorithms, we develop a city-level HSR strength index. This approach diverges from the commonly used multi-period difference-in-differences (DID) specification, allowing us to better address heterogeneity and discontinuity issues in identifying HSR effects. Thirdly, by leveraging the specific structure of the HSR network, we analyze how cities are interconnected and, for the first time, discuss the impact of “HSR-catalyzed supervision pressure” on firms’ pollution performance. Our findings show that firms exposed to higher HSR service intensity are more likely to reduce their SO2 emissions, a result that remains robust across various checks and other pollutants. We propose an intercity interaction story, predicting that HSR facilitates spillovers among city groups, thereby increasing environmental supervision pressure from neighboring cities in the HSR network. In further empirical analysis, we identify three specific sources of supervision pressure: peer pressure, vertical pressure, and public pressure.