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This paper investigates the relationship between technological finance, high-quality economic growth, and financial stability. Based on data of 30 provinces (including autonomous regions and municipalities) collected between 2004 and 2017, this paper adopts the method of factor analysis to construct comprehensive indexes of technological finance and financial stability before calculating green total factor productivity as the index of high-quality development, using the CRS Multiplicative Model. Then it constructs the spatial SAC model and PVAR model for analyses of the just-mentioned relationship based on the total sample of the nation and regional samples in eastern, middle, and western China, respectively. The results reveal that (1) All samples, whether the total national samples or regional samples of eastern, middle, and western China demonstrate the positive influence of technological finance on high-quality economic development, with an obvious spatial spillover effect. The impact factor is the highest in the eastern region, while the western region holds the lowest factor among the three. (2) Judging by the general national sample, technological finance has an obvious negative shock effect on financial stability within a short period, but the effect gradually dwindles as time goes by. This rule applies to the sample of the eastern region, as its technological finance poses a short-time negative shock effect on financial stability, before gradually diminishing to 0. Neither western nor middle regions have displayed an obvious shock impact on financial stability. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The problem of determining an optimal benchmark to inefficient decision-making units (DMUs) is an important issue in the field of performance analysis. Previous methods for determining the projection points of inefficient DMUs have only focused on one objective and other features have been ignored. This paper attempts to determine the best projection point for each DMU when the inputs and outputs data are in stochastic form and presents an alternative definition for the best projection by considering three main aspects: technical efficient, minimal cost, and maximal revenue as much as possible. Considering the important role of the electricity industry in the economic growth of each country, a practical example has been implemented on 16 regional electricity companies in Iran in 9 consecutive periods. The efficiency score along with the projection points of the three technical models (BCC model of Banker et al. (1984)), cost, and stochastic revenue are compared with the projection point obtained from the model presented in this article, which simultaneously meets these three objectives, showing the improvement of companies' performance. [ABSTRACT FROM AUTHOR]

Smart city is a brand-new city form, in which information and communication technologies are utilized to sense, analyze, and integrate the key information of city operation core system, so that intelligent responses can be immediately and effectively taken to various demands including people's livelihood, environmental protection, public safety, city services, and industrial and commercial activities. Digital economy is a mixed economy with the coexistence of multiple business models and diversified value creation models based on the information and communication technologies and in the digital economy, many things are undergoing huge changes, and their corresponding economic rules also need to be adjusted. On the basis of analyzing previous research works, this paper expounded the research status and significance of smart city's resource scheduling and strategic management, elaborated the development background, current status, and future challenges of digital economy, introduced the methods and principles of city-level spatiotemporal data model and spatial full factor coding, formulated resource scheduling strategies for smart city based on digital economy, explored the dynamic fusion, storage, and update of smart city's multisource heterogeneous data, conducted the information display and analysis of multilevel smart city, proposed strategic management approaches for smart city based on digital economy, analyzed the integrated implementation model of shared resource scheduling and people-oriented social management, and discussed the economic growth factors and standardization mechanism of smart city under the background of digital economy. The results of this study provide a reference for further research studies on the resource scheduling and strategic management of smart city under the background of digital economy. [ABSTRACT FROM AUTHOR]

Over the past three decades, China has experienced rapid economic growth along with a rapid increase in urbanization and living standards, leading to a boom in infrastructure demand. A large part of China's newly constructed infrastructure is through urban construction; thus, cities have become a major source of material consumption and carbon emissions. Understanding the relationship between material consumption, carbon emissions, and the economic growth of cities is key to ensuring that the construction of infrastructure satisfies the needs for both economic development and dematerialization. In this study, we first accounted for material consumption and the carbon emissions of infrastructure construction of 34 cities in Northeast China and characterized spatial and temporal changes from 2010–2017. The material use and carbon emissions of infrastructure construction declined by 34.6% and 30.2% during this period. Specifically, material consumption decreased from 305.2 million tonnes to 199.6 million tonnes, and carbon emissions decreased from 77.7 million tonnes to 54.3 million tonnes. Furthermore, we used a decoupling indicator to evaluate the decoupling of material consumption or carbon emissions from GDP in these cities. We found that most cities have achieved the absolute decoupling of material consumption and carbon emissions from GDP over the study period. Finally, we proposed several policy recommendations for promoting the sustainable development of the infrastructure of cities. To ensure that cities realize low-carbon urbanization, policymakers need to promote modular buildings and low-emission construction materials. This paper also serves as a practical reference for the improvement of relevant materials and carbon emissions management strategies for other developing regions. [ABSTRACT FROM AUTHOR]

Based on the data of Chinese enterprises that entered the Fortune 500 list in 2015, this paper utilizes the eclectic model to construct the inter-city association network. Using the network analysis method, the spatial connection characteristics of 311 inter-city networks at prefecture level and above and 20 urban agglomerations networks in China are examined, respectively. The research found the following: (1) the overall connectivity of city network is poor, the centripetal concentration is strong, and the network is not complete. The city network structure shows three tendencies, with a concentration in political centers, a concentration in coastal areas, and a concentration in resource-based cities. The external economic dependence of each node city in national city network is high, and the city network structure has distinctly flattening characteristics. (2) Network function of cities is obviously different in multiscale region. Large cities and regional centers have more balanced function systems than the small- and medium-sized cities do. (3) The network of urban agglomerations is characterized by decentralization of power, differentiation of status, and dependence on external connections. The radiation effect of three major urban agglomerations in coastal China is strong, but the radiation effect of other urban agglomerations needs to be strengthened. (4) Both city networks and agglomeration economies have positive impact on economic growth of the city. The economic performance of city networks is differentiated between urban agglomeration cities and nonurban agglomeration cities, as well as between cities of different scale levels. This study provides new evidence for understanding the spatial relations and expansion of Chinese city networks. [ABSTRACT FROM AUTHOR]

This paper evaluates the impact of the development of the logistics industry on economic growth based on panel data of 21 cities in Guangdong Province in China from 2007 to 2019. Using the overall entropy method, the comprehensive development index of the logistics industry is constructed to capture the performance of the logistics industry. On this basis, by using Moran's index, we measure the spatial agglomeration effect of the logistics industry. Furthermore, direct and spatial spillover effects are also obtained. The estimation results of the spatial Durbin model (SDM) reveal that the elasticity coefficient of the effect of the comprehensive development level of the logistics industry on economic growth is 0.2590, which is significant at the 1% level. In addition, the coefficient of the direct effect of the logistics industry on local economic growth is 0.4074, and the coefficient of the spatial spillover effect on the economic growth of the surrounding areas is 0.3596, which are both significant at the 1% level. These results indicate that the development of the logistics industry can not only improve local economic growth but also promote the economic growth of the surrounding regions. [ABSTRACT FROM AUTHOR]

The influence of cultural industry competitiveness on economic growth is analyzed by using grey relational degree method. Then, the influence of cultural industry on the three industries is analyzed and compared in the same way. On this basis, further from the cultural industry, the impacts of core layer, outer layer, and related layer on economic growth were compared and analyzed. Finally, the economic growth model is used to measure the impact of investment, labor, and innovation in cultural industry on economic growth. The results show that cultural industry has a great influence on economic growth. The cultural industry has an obvious driving effect on the tertiary industry. The correlative layer of cultural industry has the greatest influence on economic growth. Cultural industry innovation has a huge pulling effect on economic growth. The SPSS software was used to process the data, and the data indicators were screened. Finally, the grey relational degree model was constructed. Then, the improved diamond model was used to select the influential factors of the development of cultural industry, and the main influencing factors were found out through the grey relational degree analysis. This paper analyzes the factors affecting economic benefits and puts forward countermeasures. The results show that it is of great significance to pay attention to the development of cultural manufacturing industry in cultural industry and promote cultural innovation to promote economic growth. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, which was first reported at the end of 2019, has had a massive impact on the Chinese economy and society. The pandemic has seriously tested the emergency management capabilities of the Chinese government regarding public health. Based on the panel data of 31 provinces in China for the period of 2006–2019, this paper examines the impacts of government public health spending on regional economic growth. Furthermore, the possibility of spatial spillover effects of government public health spending is investigated through spatial econometric analysis. Government public health spending and regional economic growth have significant positive spatial correlation and spatial agglomeration effects. The indicator of government public health spending significantly promotes regional economic growth. In addition, it significantly promotes the economic growth of neighboring areas through certain spatial spillovers. [ABSTRACT FROM AUTHOR]

With the shortage of resources and the increasingly serious environmental pollution in China, green innovation has become a sustainable competition for a region. The Yangtze River Economic Belt (YREB) strategy is one of the most important strategies for the sustainable development of China's economy under the new normal. Green innovation plays a linking role in the resources exchange and trade flow in YREB, and it is also the foundation and guarantee to implement the YREB strategy. The global environmental pollution and the weak recovery of world economy make the traditional extensive economic growth model unsustainable. Sustainable economic growth should focus on the quality of development and its external costs to the environment. In order to implement the concept of sustainable development, the improvement of logistics ecological efficiency is related to the quality of ecological civilization construction. Therefore, it is of theoretical and practical significance to study the measurement, evolution, and driving factors of coordinated development level of regional green innovation system. This paper proposes a super-slack-based measure (super-SBM) data envelopment analysis (DEA) model to measure the green innovation efficiency of 11 provinces and cities in YREB from 2008 to 2017, mastering its spatial and evolutionary characteristics, and conduct empirical analysis on the influencing factors. The empirical results indicate that economic development, government support, and industrial structure upgrading are the leading forces to directly enhance the green technology innovation ability of cities in the Yangtze River Economic belt and play the core driving role of green innovation. To further enhance the capacity of urban green innovation in the Yangtze River Economic belt, we will increase the government's support for green innovation, optimize the environmental governance model, promote the green upgrading of industrial structure, and enhance the enthusiasm of enterprises for green innovation. [ABSTRACT FROM AUTHOR]

Whether financial inclusion and economic growth can sustainably release poverty alleviation effects in long term has been the focus of academia and government sector. This article uses provincial panel data from 2004 to 2019 to examine the dynamic nonlinear connectedness between the financial inclusion, economic growth, income inequality, and poverty alleviation; the main objective is to reveal the direction and intensity of the long-term and short-term impact of each factor on poverty alleviation. By building a panel vector autoregression model (PVAR), the comparison analyses of national, eastern, central, and western sample groups verify the existence of dynamic nonlinear connectedness among the four variables. The study found that there is complex bidirectional causality between these variables, financial inclusion has the long-term impact on promoting poverty alleviation in China, the impact of economic growth is relatively weak, and income inequality has weakened the positive impact of financial inclusion on poverty alleviation. Through the analysis of impulse response function, variance decomposition, and time-varying nonparametric estimates in different economic regions, we find that the impact of financial inclusion on poverty alleviation presents a U-shaped characteristic, and the contribution of financial inclusion to poverty alleviation in western regions is significant, but poverty reduction in eastern and central region mainly depends on economic growth. For policymakers, financial inclusion can be an effective way to alleviate relative poverty, but the poverty governance should focus more on reducing income inequality in China. [ABSTRACT FROM AUTHOR]

The Chinese economy has developed rapidly since the reform and opening up, but economic growth in Northeast China has declined dramatically after the 21st century. In this context, exploring the characteristics of economic and industrial fluctuations in the northeast of China and their relationship is beneficial to alleviating economic fluctuations and promoting stable economic development from the perspective of industrial development. The relationship between economic and industrial fluctuations in the three provinces of Northeast China was reexamined from the angle of fluctuation components with the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm. The results obtained are as follows: (1) In the three northeastern provinces of China, economic fluctuations were almost free from the influence of the primary industry, most affected by the secondary industry, and gradually influenced by the tertiary industry after the 21st century. (2) Regarding the short-term business cycle of each province, economic development was the most stable when the market and government participated in the development of the secondary industry simultaneously. (3) The midterm business cycle of Jilin Province was affected by the investment of equipment in secondary and tertiary industries, while that of Liaoning Province was affected by the investment of equipment in the secondary industry. (4) Investment in the equipment of the secondary industry and the construction of secondary and tertiary industries was the key to maintaining the stability of long-term business cycle in Heilongjiang Province, and that in the construction of secondary and tertiary industries was the key to maintaining the stability of long-term business cycles in Jilin and Liaoning Provinces. [ABSTRACT FROM AUTHOR]

Aiming at solving the problem of system external impact on China's general aviation industry, combining functional theory and grey system theory, and applying Bayesian network reasoning technology, a grey Bayesian network reasoning prediction model of system impact and system control is established. Based on the dynamic deduction of the functional analysis factor of system impact evolution, the flight time of general aviation production operation is selected to predict the development trend of the system. Based on the current period information of the general aviation industry, the grey Bayesian network inference prediction model is used to predict the current and future trends, so as to predict the economic development trend of the general aviation industry in China. The prediction results are more accurate than those of other existing models. [ABSTRACT FROM AUTHOR]