Hong Xuefei

Ms. Hong Xuefei


Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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LLLi Li
Li Li
QLQuanqi Liu
Quanqi Liu
WJWang Jun
Wang Jun
HXHong Xuefei
Hong Xuefei
Using listed enterprises in China’s heavy pollution industry from 2009 to 2013, this study tests the relationship between marketization degree, carbon information disclosure, and the cost of equity financing. The results show that, regardless of marketization degree, the overall level of carbon information disclosure of listed enterprises in China’s heavy pollution industry is low. The content of carbon information disclosure is mainly non-financial carbon information, and the financial carbon information disclosure is very low. The cost of equity financing is different in areas with different marketization degrees, specifically speaking, the cost of equity financing is lower in regions with a high marketization degree than that of a low marketization degree. Carbon information disclosure, non-financial carbon information disclosure, and financial carbon information disclosure are negatively correlated with the cost of equity financing. The marketization degree has strengthened the negative correlation between carbon information disclosure, non-financial carbon information disclosure, financial carbon information disclosure, and the cost of equity financing, respectively.

10 May 2016 in Sustainability
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Journal Article
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LLLi Li
Li Li
HXHong Xuefei
Hong Xuefei
DTDengli Tang
Dengli Tang
MNMing Na
Ming Na
To gain a greater understanding of the spatial spillover effect of greenhouse gas emissions and their influencing factors, this paper provides a spatial analysis of four gas pollutants (CO2 emissions, SO2 emissions, NOx emissions, and dust emissions). Focusing on China, the paper also explores whether the four gas pollutants are influenced by the emissions of neighboring regions and other possible sources. The paper uses a global spatial autocorrelation analysis, local spatial association analysis and spatial lag model for empirical work. The results suggest that CO2, SO2, and NOx emissions show significant positive results for both the spatial correlation and space cluster effect in provincial space distribution.CO2 and NOx emissions have a significant positive spillover effect, while the SO2 emissions’ spatial spillover effect is positive but not significant. Economic growth and urbanization are the key determinants of CO2, dust, and NOx emissions, while energy efficiency and industrialization do not appear to play a role. This raises questions about the method of examining the spatial relationship between gas pollution, economic growth and urbanization in the future.