Public psychological distance and spatial distribution characteristics during the COVID-19 pandemic: a Chinese context.

The COVID-19 pandemic is a public health emergency, which continues to have a significant impact on the functioning of society and the public's daily life. From the perspective of psychological distance (PD), this study used descriptive, differential, and spatial autocorrelation analysis methods to explore the cognitive distance, emotional distance, expected distance and behavioral distance of the Chinese public in relation to the COVID-19 pandemic. An analysis of 4042 valid sample data found that: (1) The event emotional distance and subject emotional distance were both furthest from the event and subject psychological distance dimensions, and anger about the event was the strongest. (2) The government was the most appealing subject in the process of pandemic prevention and control, but at the same time, the public's sense of closeness to the government was also lower than that of the other three subjects, e.g., medical institutions. (3) Different pandemic regions showed significant differences in PD. Mean scores of PD in each risk region were as follows: High-risk regions > medium-risk regions > low-risk regions. (4) From a global perspective, no spatial autocorrelation was found in PD. However, from a local perspective, high-value regions (provinces with distant PD) are mainly concentrated in the southern regions (Guizhou, Guangxi, Hainan, Jiangxi), and low-value regions (provinces with close PD) are mainly concentrated in North China (Shanxi, Hebei, Beijing). Combined with the relevant conclusions, this paper put forward policy recommendations.

The Dual Impacts of Green Credit on Economy and Environment: Evidence from China

Green credit is regarded as an important means to promote sustainable growth. Based on the provincial panel dataset of China from 2007 to 2017, this paper investigates the dual impacts of green credit on the economy and environment, and it establishes mediating effect models to analyze the Porter hypothesis. The results show that the green credit policy significantly improves economic performance and reduces pollutant emissions. The above results are robust to employing methods with alternative variables and instrumental variables. Second, the green credit policy contributes to innovation;that is, the green credit increases the innovation scale and improves innovation efficiency. The results of mediating effect models suggest that the Porter effect of green credit can be achieved by improving innovation efficiency. The findings of the current study indicate that the green credit policy helps achieve the win–win situation for economic goals and environmental targets.