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Shrinkage in China's cities has gradually received increasing attention. Specifically, county-level shrinking cities are numerous and widely distributed. City shrinkage even appears throughout Zhejiang Province, which is highly developed and has stable economic growth. County-level shrinking cities resulting from regional competition can still maintain long-term and stable economic growth, but their economic growth lags behind the whole competitive region. We identified five county-level shrinking cities in Zhejiang Province, and characterized the shrinkage phenomenon in Changshan County using census, nighttime lighting (NTL), and Tencent Location Big Data. City shrinkage resulted from the comprehensive effects of declining traditional industries, backward per capita income, highly skilled labor force shortages, and population age structure changes. Given the shrinkage status of Changshan, we proposed countermeasures and suggestions including aspects of industrial development, urban planning, social governance, and care for the elderly. [ABSTRACT FROM AUTHOR]

China’s domestic labor market has limited demand for tertiary graduates due to an unbalanced industrial structure, with a weak contribution to economic performance over the past decade. This study estimates the asymmetric eects of higher education progress (highly educated employed workforce), higher education utilization (highly educated unemployed workforce), and the separate eects of higher education utilization interactions with high-tech industries on economic growth in China from 1980 to 2020. Using a Nonlinear Autoregressive Distributed Lag (NARDL) model, this study finds that the expansion of higher education progress (the employed workforce with higher education) promotes economic growth, while contraction of higher education progress (employed workforce with higher education) reduces economic growth. Likewise, an increase in higher education utilization (the unemployed labor force with higher education) suppresses economic growth, while a decline in the higher education utilization (the unemployed labor force with higher education) promotes economic growth. The study also found that the expansion of high-tech industries and government spending on education significantly stimulate economic growth. The moderating role of higher education utilization (unemployed labor force with higher education) in the impact of high-tech industries on economic growth is significantly positive. This study strategically proposes that China’s higher-educated unemployed labor force can be adjusted to high-tech industries, which need to be developed equally in all regions. Moreover, the country is required to invest more in higher education and the development of high technological industries across all regions, thus may lead to higher economic growt [ABSTRACT FROM AUTHOR]

Background: The progress of green credit in China is accelerating, but its development is uneven and insufficient in different regions. And whether the issuance of green credit can effectively promote the improvement of the environment and economy is not well understood. Objective: Previous research has found that green credit promotes economic growth through improvement of the industrial structure and green technological innovation. However, these studies have not considered the positive externality of environmental improvement even though environmental improvement and economic growth are requirements of the sustainable development concept. Methods: We use the chain-mediated model to estimate the impact of green credit issuance on the economic growth of different provinces since the large-scale implementation of green credit in China with data from 2008 to 2016. Results and conclusion: This paper shows that the issuance of green credit can improve labor supply rather than labor productivity through the improvement of air quality to achieve regional economic growth. Such a chain-mediated path is different from the economic growth caused by industrial structural adjustment and green technology innovation. At the national level, every 1% increase in green credit issuance relative to industrial loans will increase the per capita gross domestic product (GDP) by approximately 4.6 yuan, or 0.012%, through air quality and labor supply, accounting for 2.875% of the total effect. Heterogeneity analysis indicates that due to regional industrial structure differences and diminishing marginal effects, the impact of green credit is stronger in the western region than in the eastern and central regions. For every 1% increase in the proportion of green credit issuance relative to industrial loans, the per capita GDP growth achieved through the chain-mediated path is approximately 30.17 yuan in the western region, approximately 6.6 times greater than that at the national level. Within a 95% confidence interval of 5000 bootstrap samples, this path is found to be true, and the chain-mediated effect accounts for approximately 12.96% of the total indirect effect. Limitations: The limitation of this paper is the measurement of green credit. Although green credit has a large volume, it remains underdeveloped, and there is a lack of perfect indicators. Most existing studies have adopted only alternative or reverse indicators to measure the issuance of green credit. For example, this paper takes the interest expenditure of six high-energy-consuming enterprises as the reverse indicator, which may to a certain extent lead to the overestimation of the issuance of green credit and its impact on the environment and economy. Future research can accurately explore the performance of green credit on the basis of its mature development. [ABSTRACT FROM AUTHOR]

Industrial structure optimization is an important explanatory variable of economic growth. The allocation of production factors among industries affects the evolution of industrial structure and then acts on economic growth. Labor force is one of the most important factors of production. In recent years, there has been a significant wage difference between different industries in China's labor market, and the employees have shifted from low-wage industries to high-wage industries. Using the sample data of 282 prefecture-level cities from 2008 to 2018, this paper tests whether this wage-guided labor industry allocation will affect economic growth and whether there is an intermediary effect of industrial structure optimization. The empirical results show that the allocation of labor force to high-wage industries not only directly hinders economic growth but also indirectly hinders economic growth through the intermediary effect of industrial structure optimization. Furthermore, this paper makes a comparative study in different regions. The research conclusion shows that promoting the optimization of industrial structure and economic growth depends on correcting the price distortion of labor market and guiding the cross-industry rational allocation of labor force. [ABSTRACT FROM AUTHOR]