This paper examines the spatial spillover effects of public transportation infrastructure on regional economy in Northeast China, the “rust belt” region in China. The dataset consists of socioeconomic data from 47 cities in the area during the period of year 2005 through 2015. Accessibility is used as an explanatory variable to reflect the influence of infrastructure on economic development. In order to avoid the endogenous, queen contiguity matrix is used to define the spatial weight matrix. In the paper, the dynamic panel data model is also used to explore the effects of high‐speed railways in the whole study area and attempted to confirm the spatial differences among Heilongjiang Province, Jilin Province, and Liaoning Province. The results show that the high‐speed railways increase the cities’ connection in terms of accessibility, and a significant positive spillover effect exists after the construction of high‐speed railways (HSR), indicating the extensive economic benefits of HSR construction, despite of the overall economic difficulty experienced by this region.

The global economic downturn and the new normal status of China’s economy have revealed that the Northeastern region of the country is facing challenges due to poor adaptability and weak regional economic resilience. In regard to the regional cities of China’s municipal-administered county system and from the perspective of the relationship between the economic resilience of the central-cities and the outer-suburbs, it is helpful to explore the characteristics of the regional economic resilience in Northeast China from 2007 to 2018. We find that: (1) The economic resilience of the central-cities and outer-suburbs in Northeast China has deteriorated. Compared with the central-cities, the economic resilience of outer-suburbs has weakened even more. (2) The types of regional economic resilience of the central-cities and outer-suburbs of Northeast China have diversified and weakened. The main types of economic resilience have changed from city-prospered-suburb-prospered and city-balanced-suburb-prospered to city-balanced-suburb-balanced and city-declined-suburb-declined. There are differences in the types of municipal economic resilience that are affected by changes in the economic resilience levels of central-cities and outer-suburbs. (3) It is further confirmed that the industrial structure has an important influence on the resilience of the regional economy. The economic resilience of the outer-suburbs in the Northeast China appear to be more vulnerable and more heavily influenced by changes in the proportion of the secondary industry than the central-cities.

Currently, most studies on the factors affecting sleep quality have used logistic regression or multiple linear regression to identify such factors, there are same drawbacks in these methods, the structural equation modeling (SEM) can compensate for these deficiencies. A total of 2341 students from three universities in Hainan, China, participated in the cross-sectional survey. The Pittsburgh sleep quality index (PSQI) was used to evaluate sleep quality. A self-administered questionnaire was provided to collect data for the symptom checklist-90 (SCL-90) and the internet addiction test (IAT), as well as other potential or hidden factors affecting sleep quality. SEM was used to estimate the important factors affecting sleep quality, and to explore the particular contributions of the identified factors. The types of hidden factors affecting sleep quality were, in descending order, psychological (0.308), behavioral (0.289), physiological (0.250), and environmental (0.019) factors. More specifically, higher scores on the SCL-90 (0.780) caused the biggest difference in sleep quality, followed by health status (0.601), the frequency of late sleeping (0.574), internet addiction (0.530), and the dormitory environment (0.470). The results provide reliable means for the improvement of sleep quality among college students.