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Population aging has become a social issue of concern to the whole world, and as the world's most populous country, how to cope with population aging will be a hot issue that all sectors of Chinese society must think about. This paper uses provincial panel data from 30 provinces in China from 2000 to 2021 to study the relationship between population aging and economic development based on the perspective of health expenditure. The DIFF-GMM model, the fixed effect model (FE), and fixed effect instrumental variable model (FE-IV) are used to test this study. The following two conclusions are drawn from the empirical study: (1) population aging has a significant inhibitory effect on economic development, while health expenditures have a significant promotional effect on economic development; and (2) increased health expenditures help to alleviate the negative impact of population aging on economic development. However, the deepening of population aging will likewise inhibit the positive effect of health expenditure on economic growth. Based on the conclusions of the study, it is recommended that the government and society should continue to increase spending in the field of health protection, encourage and guide residents to carry out self-care, and moderately increase personal health expenditure, to promote economic development with healthy bodies and realize the goal of "Healthy China". [ABSTRACT FROM AUTHOR]

With the development of China's economy entering a new stage, the quality of life, which centers on the well-being of residents, provides an essential hand in promoting the transformation of the regional economy from high-speed development to high-quality development. Based on a panel threshold regression model, we examine in this paper whether quality of life helps regional economies realize developmental convergence. The research shows that: (1) The quality of life overall can promote regional economic development and passes the series test with relatively robust results. (2) The quality of life has a non-linear effect on regional economic growth, which is mainly manifested in the fact that the impact is more significant in regions with higher levels of quality of life and weaker in regions with lagging quality of life and may widen the gap between regions at the same time. (3) We categorize the study regions to test further regional heterogeneity based on regional location and development status. At the Quality of Life Level-I regions, their influence on economic development has a more substantial pulling effect. Therefore, each region should seize the strategic opportunity to improve the quality of life, focus on the balanced development of the quality of life, strengthen policy support and social security, and strive to promote the coordinated development of China's regional economy. [ABSTRACT FROM AUTHOR]

To stimulate economic growth, China has launched multiple economic stimulus plans in recent years, intensifying corporate debt financing and subsequently elevating the leverage levels. Addressing and effectively reducing the leverage levels of our country's enterprises has emerged as a pressing issue in the trajectory of our economic development. This paper primarily investigates the drivers, pathways, and mechanisms for reversing the over-leveraged values of enterprises. Key findings include: (1) Excessive indebtedness exerts a negative impact on corporate value, with the suppressing effect intensifying as the degree of over-leverage increases; (2) Over-leveraged enterprises can effectively decrease their debt levels and enhance their value through private placement. Further research suggests that this mechanism operates by amplifying the operational leverage of over-leveraged enterprises post private placement and alleviating financing constraints, thereby elevating corporate value. (3) Compared to non-state-owned enterprises, state-owned enterprises exhibit higher levels of indebtedness. Among over-leveraged firms, enhancements in corporate governance and increased investment efficiency can positively transform corporate value. This study offers valuable insights for the ongoing supply-side structural reforms and governance guidance from the regulatory bodies. [ABSTRACT FROM AUTHOR]

This paper aims to study the relationship between regional logistics efficiency and economic development in 31 provinces of China and analyze their coupling coordination. To comprehensively evaluate the coordination between logistics and the economy, we introduced external indicators, such as carbon emissions, based on traditional evaluation indicators. We constructed an evaluation index system to coordinate regional logistics efficiency and economic development. The research approach used in this paper is the cross-DEA method, and data from 2010 to 2019 were selected for empirical calculation. The research findings indicate that Eastern and Northern regions of China show higher logistics efficiency, while Northwestern and Southwestern regions exhibit lower logistics efficiency. Coastal areas have relatively higher economic development levels compared to inland areas. Regarding the coupling coordination between logistics efficiency and economic development, different regions show temporal fluctuations and spatial disparities. Some regions demonstrate higher coordination between logistics efficiency and economic development, while others show lower coordination. Additionally, as the economy experiences rapid growth, logistics efficiency also improves, but the level of coordination varies among different provinces. [ABSTRACT FROM AUTHOR]

For a long time, China 's extensive economic development model has produced a large amount of emissions, which has brought indelible damage to the environment. Green development is of vital importance for China to achieve high-quality development, and it is the core of alleviating environmental problems and promoting sustainable development. How to achieve China 's green development requires us to evaluate the level of green development in China 's provinces and analyze the reasons. In this study, an evaluation index system including undesired output of green development efficiency is constructed, and then the Supe-SBM model is used to assess the green development efficiency of 30 Chinese provinces. This paper also discusses the spatial and temporal differences as well as the factors affecting green development efficiency of green development efficiency among provinces. The findings demonstrate: (1) The green development efficiency in the eastern region is the highest, followed by the western region, while the central region has the lowest, but they all show a downward trend. (2) The spatial characteristics of green development efficiency are remarkable, according to the Global Moran's I index. However, the results of local spatial agglomeration demonstrate "small agglomeration and large dispersion," with the majority of provinces exhibiting L-L agglomeration. (3) Technological Progress, Opening Up, Urbanization Level are positively correlated with the green development efficiency. Industrial Structure, Financial Development, Energy Structure and green development efficiency are significantly negatively correlated, while Environmental Regulation shows no significant impact. [ABSTRACT FROM AUTHOR]

Since 2020, China has been dedicated to the goal of "carbon peak and carbon neutrality" in the international community, demonstrating its commitment to energy conservation and emissions control. In 2021, in response to the guidance of the State Council, all provinces in China included the creation of a low-carbon economic system as one of their key development goals. This paper aims at investigating the low-carbon economic development efficiency and the redundancy of inefficient areas of Guangdong Province by using the three-stage DEA-Malmquist index model. Panel data of 21 cities from 2011 to 2020 in Guangdong Province were selected. Results revealed that the low-carbon economic development efficiency in the whole province rises, but the growth rate has slowed down in the past three years. Pearl River Delta area is better-developed in low-carbon economy than others. It is recommended to improve the efficiency of scale, make use of environmental advantages and develop energy-saving and emission reduction technologies. [ABSTRACT FROM AUTHOR]

China's economy has shifted from the stage of high-speed growth to the stage of high-quality development. This paper selects panel data of 30 provinces, municipalities directly under the Central Government and autonomous regions (except Tibet) in mainland China with the time dimension of 2006–2016, selects indicators from five dimensions of innovation, coordination, greenness, openness and sharing, uses principal component analysis to construct a system of indicators of high-quality economic development, and uses the spatial Durbin model to empirically the impact of government investment behavior in the three industries on the regional economic high-quality development was studied. The results show that: first, there is a significant positive spatial correlation between China's economic quality development. Second, government investment in different industries has different effects on the quality development of the economy. Investment in the tertiary industry can boost employment, raise income level, promote economic quality development, and enhance sharing, coordination and innovation; investment in the secondary industry can enhance innovation, but because of the "crowding-out effect", it will reduce openness and sharing, and is not conducive to promoting economic quality development; investment in the primary industry can Investment in the primary industry can significantly improve coordination, but it will reduce innovation, greenness, openness and sharing, which will also have a negative impact on the overall high-quality economic development. Third, there is a significant spatial spillover effect of government investment behavior on regional economic quality development, and the economic quality development of this region will have an impact on neighboring regions. Finally, based on the research results, this paper puts forward countermeasure suggestions for promoting high-quality economic development. [ABSTRACT FROM AUTHOR]

Currently, there is a large deviation between official road freight data and real road freight performance at a subnational level in China. In order to deal with this deviation, the new concept of local freight tonnage and ton-kilometers is presented in this paper based on the territoriality principle, where either the origin or the destination of goods transported is local. Also, the statistic procedures and estimation models of the local freight tonnage and ton-kilometers are proposed based on five accessible basic datasets. Finally, an empirical study in Sichuan province of China is conducted. The statistical results show that there is a large amount of local freight transported by local non-commercial trucks and non-local trucks, which is ignored in the existing road freight statistics. Especially, the higher the level of local economic development, the greater the deviation between the official road freight data and the real road freight performance at a subnational level. [ABSTRACT FROM AUTHOR]

This paper constructs a theoretical model of biased production decisions due to the import of environmental intermediate goods. Additionally, it analyzes the influence of these imports on CO2 emissions based on the trade and CO2 emission data of Chinese prefecture-level cities from 2000 to 2016. Furthermore, it empirically explores how environmental intermediate imports affect CO2 emissions. The study found the following: first, the import of environmental intermediate goods can effectively reduce CO2 emissions; this conclusion still holds under robustness and endogeneity tests. Second, the carbon emission reduction effect related to the import of environmental intermediate goods is affected by differences in geographical location, environmental pollution, sustainable development ability and government efficiency. Third, the mechanism test found that the import of environmental intermediate goods exerts emission reduction effects through the green technological innovation and industrial structure upgrading mechanisms. The conclusions of the research in this article provide a reference for coordinating trade development and environmental protection. [ABSTRACT FROM AUTHOR]

Background: China has been exploring a sustainable development path that harmonizes economic growth and environmental protection, targeting to build a beautiful China. The role of green finance in adjusting the misallocation of financial resources and leading the green sustainable development of the real economy is receiving increasingly more attention. Currently, green credit accounts for more than 90% of the total green finance funding in China and constitutes the most significant component of the green finance matrix. Whether green credit effectively promotes the green and sustainable development of the regional economy largely determines the success of China's economic green transformation. Objective: Existing studies of green credit mainly focus on its influences on financing, investment, and emission reduction of environmental pollution industries or companies. Extending the literature by exploring whether green credit is effective in promoting green sustainable development and what impact green credit exerts on the upstream (energy inputs), midstream (technological innovation), and downstream (pollution outputs) stages of the green sustainable development value chain, is the leading research objective of this paper. Methods: This paper discusses the impact of green credit on green sustainable development based on city panel data from 2012 to 2019. The level of green sustainable development is calculated by the GML index based on SBM directional distance function. The city-level green credit scale is calculated from the green credit issued by banks, weighted by the density of bank branches in a city. Synthetic control methods are employed in the robustness analysis to reduce the impact of endogeneity issues. Results and conclusion: The results of this paper indicate that green credit can promote green sustainable development and the impact gradually strengthens over time as the incremental implementations of complementary policies with substantial constraints and incentives, through which pollution control and economic growth achieve a "win-win" situation. Furthermore, the results indicate that green credit reduces the overall amount of energy inputs while optimizing the energy input structure. However, green credit does not boost the green technological level and even crowds out high technical value green innovations. Besides, the pollution reduction effects of green credit are associated with the strength of green credit constraints and the importance of pollution industries in the local economy, which means green credit performs better pollution reduction effects in regions with relatively strong green credit binding effects or in regions where pollution industries are not local economic pillars. The empirical results are further validated through robustness tests, including changing scope and measurement variables and applying the synthetic control method. Limitations: Although this paper provides valuable contributions to the research area of green credit and green sustainable development, specific limitations exist in the current study. Firstly, as the official information disclosure of green credit in China is not sufficient, existing studies, including ours, could only use estimation methods through different perspectives to measure green credit, which is overall logical and reasonable but may lose some accuracy. Secondly, since there might be a certain degree of lag in the effect of green credit on the economy, the dynamic impact and long-term effects of green credit deserve further study. Thirdly, considering the characteristics of the Chinese administrative systems, introducing the behavior of local governments and local officials into the analysis of green credit and green sustainable development could be valuable. [ABSTRACT FROM AUTHOR]

Against the background of globalisation and state rescaling, promoting decentralisation and enhancing local governance capacity have become prioritised objectives of transnational city-to-city partnerships mainly between developed and developing countries. However, considering the critical debates on Global East's uniqueness, two questions emerge when studying the transnational partnerships of Chinese cities. (1) Are Chinese cities' partnership establishments and objectives remarkably different from the existing international body of knowledge? (2) In China, whether decentralisation and local governance are promoted by city-to-city transnational partnerships as well? To cope with the questions, this paper examines 28 Chinese world cities' partnership establishments and objectives and reaches two conclusions. (1) With the objective of economic development, Chinese cities have consistently maintained strong connections with cities in both the developed and developing countries. (2) Chinese cities' transnational partnerships do not observably promote decentralisation, and China's political decentralisation is much more unstable than its economic decentralisation. Overall, both the binary partnership establishments and the dual-track decentralisation in political and economic aspects are highly embedded in China's interstitial and transitional position as a Global East country. [ABSTRACT FROM AUTHOR]

While China's digital trade is developing rapidly, it is facing the problem of uncoordinated and uneven regional development. In order to explore countermeasures to bridge the differences in regional digital trade, this paper first measures the development level of digital trade in 11 provinces of the Yangtze River Economic Belt through entropy-weighting TOPSIS. Secondly, the fuzzy set Qualitative Comparative Analysis method was used to analyze the influencing factors and improvement paths of digital trade development in various provinces of the Yangtze River Economic Belt. The research results show that: first, the current development level of digital trade is gradually weakening from east to west, especially the development of digital trade in the Yangtze River Delta region is the best, showing a large regional imbalance and uncoordinated development. What's more, the market size and urbanization have the most significant impact on the development of digital trade. Finally, we examine the reliability of the results by sensitivity analysis, and find that our ranking results are robust. In the future, China should continue to actively promote the coordinated development strategy of regional economy and participate in international digital trade exchanges and cooperation, so as to promote the coordinated and high-quality development of digital trade. [ABSTRACT FROM AUTHOR]

The dominant spatial econometric model in spatial econometrics is the parametric form, while in the realistic context, the variables often do not satisfy the assumption of linearity and have nonlinear relationships with each other. In this paper, we introduce nonparametric terms into spatial econometric models and propose the MCMCINLA estimation method for varying coefficient spatial lag models. The empirical analysis is conducted with the socioeconomic data of mainland China from 2015 to 2020 to discuss the influencing factors and spatial and temporal distribution characteristics of China's economic development under the classical spatial lag model and the varying coefficient spatial lag model with population aging as a special covariate, respectively. The results show that with the gradual aging of the population, foreign trade will inhibit the development of regional economy to a certain extent, while urbanization process, resident income, real estate development and high-tech development will have a driving effect on economic growth, and high-tech development has the strongest mobilization on regional economic development. Compared with the classical spatial lag model, the varying coefficient spatial lag model can more fully exploit the information of variables in a more realistic context and derive the variable evolution process. [ABSTRACT FROM AUTHOR]

China is a large country with rapid economic expansion and high energy consumption, which implies that the country's overall carbon emissions are enormous. It is vital to increase urban low-carbon economy efficiency (ULEE) to achieve sustainable development of China's urban economy. Digital finance is a significant tool to boost ULEE by providing a convenient and effective funding channel for urban low-carbon economic transformation. Analyzing the coupled and coordinated relationship between ULEE and digital finance is of vital importance for the sustainable development of the urban economy. This paper selects panel data of 100 cities in China's Yangtze River Economic Belt (YEB) in 2011-2019, and analyzes the research methods such as the Global Malmquist-Luenberger index model, coupling coordination degree (CCD) model, standard deviation ellipse model, gray model, and geographic detector by The spatial and temporal distribution, dynamic evolution characteristics and influencing factors of the CCD between ULEE and digital finance are analyzed. The study shows that: (1) the CCD of ULEE and digital finance grows by 3.42% annually, reflecting the increasingly coordinated development of the two systems; (2) The CCD of ULEE and digital finance shows a distribution pattern of gradient increase from the upstream region of Yangtze River to the downstream region, meanwhile, the spatial center of gravity moves mainly in the midstream region; (3) The spatial center of gravity of CCD of ULEE and digital finance is expected to move 22.17 km to the southwest from 2019 to 2040; (4) In terms of influencing factors, the influence of informatization and industrial structure on the CCD increases over time, while the influence of factors such as population development, greening, transportation, and scientific research decreases over time. Finally, this paper proposes policy recommendations for improving the CCD of ULEE and digital finance based on the empirical results. [ABSTRACT FROM AUTHOR]

Using the statistical data of 280 prefectural-level cities in China from 2011 to 2020, this paper empirically tests the relationship between digital finance and residents' income in a linear and nonlinear model based on the G-J model theory, respectively. The study aims to discuss and analyze the impact of digital finance development on income distribution in the context of the current situation of digital finance development in China and further explore how to make digital finance better regulate the income distribution of residents. The innovation of this paper is to use two nonlinear methods to verify the Kuznets effect and threshold characteristics of digital financial development affecting the income distribution of residents based on linear analysis and explore the relationship between n digital economic development the current income gap more comprehensively. The study shows a Kuznets effect of digital finance development on the income distribution of Chinese residents. Thus, most regions in China have not yet crossed the inflection point of the bell-shaped curve, and the income gap within areas will continue to increase with the development of digital finance. By constructing a threshold model, it is found that the positive effect of digital finance on income disparity may initially increase with the increase of regional economic level. Still, when the regional economic development reaches a higher stage, the effect will tend to fall back. As a result, the negative impact of digital finance development on residents' income distribution will be significantly reduced at that time. [ABSTRACT FROM AUTHOR]

The aging population is a common problem faced by most countries in the world. This study uses 18 years (from 2002 to 2019) of panel data from 31 regions in China (excluding Hong Kong, Macao, and Taiwan Province), and establishes a panel threshold regression model to study the non-linear impact of the aging population on economic development. It is different from traditional research in that this paper divides 31 regions in China into three regions: Eastern, Central, and Western according to the classification standard of the National Bureau of Statistics of China and compares the different impacts of the aging population on economic development in the three regions. Although this study finds that the aging population promotes the economy of China's eastern, central, and western regions, different threshold variables have dramatically different influences. When the sum of export and import is the threshold variable, the impact of the aging population on the eastern and the central region of China is significantly larger than that of the western region of China. However, when the unemployment rate is the threshold variable, the impact of the aging population on the western region of China is dramatically higher than the other regions' impact. Thus, one of the contributions of this study is that if the local government wants to increase the positive impact of the aging population on the per capita GDP of China, the local governments of different regions should advocate more policies that align with their economic situation rather than always emulating policies from other regions. [ABSTRACT FROM AUTHOR]

Assessing the trade network connectivity is essential for understanding the trade network structure, optimizing trade development patterns, and improving uneven trade development along the "Belt and Road" (BRI). From the perspective of connectivity, this paper integrates the frontier algorithms in network science and constructs an analytical framework to identify the mesoscale structures, including the community structure, core-periphery structure, and backbone structure embedded in the network, and further explore the structural connectivity of the BRI trade network. The results show that: (1) The BRI trade network represents a trade pattern of "one superpower, many great powers", with three major trade groups in Southeast Asia, the Middle East, and Northern Central and Eastern Europe in terms of geographical space. China is the super core of the BRI trade network, and the most considerable trade links are all centred in China. (2) Five distinctive trade blocs have formed in the BRI trade network. Nevertheless, the structure of the trade blocs shows significant geographical proximity, indicating that geographical distance still plays a vital role in the international trade system at the regional scale. (3) The BRI trade network demonstrates a significant core-periphery structure, with apparent trade clustering among the core countries within the trade network. Among them, nine countries led by China constitute the core structure, and the peripheral structure is large, reaching forty-four. (4) The trade links with China constitute the backbone structure of the whole trade network in the BRI region. In addition, the trade links related to energy trade and re-export trade are also crucial components of the BRI backbone structure. Methodologically, the analytical framework proposed for assessing the network structural connectivity has great potential to be widely applied to other disciplines and fields. [ABSTRACT FROM AUTHOR]

Under the background of global response to climate crisis and environmental pollution, environmental regulation plays an increasingly important role in green technology innovation. This paper uses data from 280 Chinese cities from 2003 to 2019 to empirically answer the question whether environmental regulation can improve the level of urban green technology innovation. It is found that environmental regulation has a significant positive effect on green technology innovation. Under the heterogeneity of economic geographical region and resource-based city, environmental regulation has positive promoting effect on urban green technology innovation. Heterogeneity results also show that environmental regulation significantly promotes green technology innovation in central and resource-based cities, but does not significantly promote green technology innovation in eastern and western cities and non-resource-based cities. Further research shows that environmental regulation can promote the level of green technology innovation through the two transmission mechanisms of government technology input and foreign direct investment. For the Chinese local government which is implementing the policy of green economic transformation, the formulation of scientific regional environmental policy is beneficial to improve the level of green technology innovation, increase government technology input and optimize the foreign investment environment. [ABSTRACT FROM AUTHOR]

At present, the digital economy, which takes information technology and data as the key elements, is booming and has become an important force in promoting the economic growth of various countries. In order to explore the current dynamic trend of China's digital economy development and the impact of the digital economy on the high-quality economic development, this paper measures the digital economic development index of 30 cities in China from the three dimensions of digital infrastructure, digital industry, and digital integration, uses panel data of 30 cities in China from 2015 to 2019 to construct an econometric model for empirical analysis, and verifies the mediating effect of technological progress between the digital economy and high-quality economic development. The results show that (1) The development level of China's digital economy is increasing year by year, that the growth of digital infrastructure is obvious, and that the development of the digital industry is relatively slow. (2) Digital infrastructure, digital industry and digital integration all have significant positive effects on regional total factor productivity, and the influence coefficients are 0.2452, 0.0773 and 0.3458 respectively. (3) Regarding the transmission mechanism from the digital economy to the high-quality economic development, the study finds that the mediating effect of technological progress is 0.1527, of which the mediating effect of technological progress in the eastern, northeast, central and western regions is 1.70%, 9.25%, 28.89% and 21.22% respectively. (4) From the perspective of spatial distribution, the development level of the digital economy in the eastern region is much higher than that in other non-eastern regions, and the development of digital economy in the eastern region has a higher marginal contribution rate to the improvement of the total factor productivity. This study can provide a theoretical basis and practical support for the government to formulate policies for the development of the digital economy. [ABSTRACT FROM AUTHOR]

The development of the digital economy is conducive to the innovative development of foreign trade and the formation of a "dual circulation" development pattern in China. Based on the panel data of 285 prefecture-level cities in China from 2005 to 2019, this paper examines the influence of the digital economy on urban export trade and its heterogeneity. And we use a mediating effect model to explore the possible mediating role of technological progress in the above influences. The results find that: (1) The improvement of the digital economy can promote cities export; (2) The promotion of the digital economy to the growth of city export scale is heterogeneous, which is more significant in the western and northeastern cities with relatively remote geographical locations, and the third-tier and lower cities with relatively backward economic development. (3) Technological progress has played a significant role in promoting the growth of export for the digital economy. Thus, it's of great importance for China to increase investment in digital economy infrastructure and pay more attention to the differences in diverse city development processes. It should also support basic research and development in information technology to promote high-quality development of China's foreign trade through the digital economy. [ABSTRACT FROM AUTHOR]

This paper empirically tests the relationship between digital finance and income distribution of residents in 280 cities in China from 2011 to 2020 using linear and nonlinear models, respectively. Based on the Greenwood-Jovanovic (G-J) theory of output grow, the empirical study shows that there is a Kuznets effect of digital finance development on the income distribution of Chinese residents, and most regions have not yet crossed the inflection point of the bell-shaped curve, and the income gap within regions will continue to increase with the development of digital finance. Furthermore, the threshold model test shows that the positive effect of digital finance on the income disparity of residents may initially increase with the increase of regional economic level. However, when the regional economic development reaches a higher stage, the negative effect of digital finance development on the income distribution of residents will be significantly reduced. [ABSTRACT FROM AUTHOR]

This paper builds an evaluation index system, uses the entropy weight method (EWM) to decide the weights and, based on the coupling coordination degree model (CCDM), it systematically studies the coupling relationship between Chinese cold chain logistics and the Chinese economy from 2010 to 2019. It performs a grey relational analysis (GRE) to explore the main factors influencing the coordinated development of the two. The results show that the coupling coordination degree between the two presents a steady upward trend, and their coupling relationship has been upgraded from 'coordination' to 'good coordination'. They also indicate that the added value in the tertiary industry, the per capita gross domestic product (GDP), and household consumption levels are the main factors affecting the development of cold chain logistics, while the per capita cold storage capacity, the turnover of road cold chain freight, and the volume of human-power employed in cold chain logistics are the main factors affecting economic development. This study makes suggestions to support the coordinated development of cold chain logistics and economy, and provides a scientific basis for further research. [ABSTRACT FROM AUTHOR]

The Yangtze River Delta urban agglomeration is the leading and demonstration area for the high-quality development of culture tourism (HDCT) in China. It is of great significance to study the spatiotemporal characteristics and impact mechanism of the HDCT for revealing the internal law of HDCT and promoting the collaborative innovation of culture tourism among cities. Based on the scientific construction of the evaluation system of HDCT, this paper made a quantitative analysis of 26 cities' HDCT by using coupling coordination degree model, Lisa spatiotemporal transition and spatial Durbin model (SDM). The results show that: The overall level of 26 cities' HDCT shows a fluctuating upward trend, and presents a "Z" pattern in space. More than 80% of the cities are at the medium and high level. Shanghai has obvious advantages in the primacy degree. There is a significant positive spatial autocorrelation among cities with high-quality of culture tourism development. The spatial clustering and proximity of the same kind are increasing, and the radiation effect is gradually obvious. The local spatial association patterns are mainly HH and LL agglomeration, and the characteristics of polarization are gradually prominent. The local spatial correlation structure of HDCT has strong stability, the transfer inertia between types is prominent, and the overall spatial evolution is lack of integration with obvious path dependence and lock-in effect. The spatiotemporal evolution of the HDCT is a complex process under the interaction of multiple factors, and there is a significant spatial spillover effect (0.256). The level of economic development, technological innovation, professional talent allocation are the three main factors. According to the dominant factor, it can be divided into economy stabilizing type, industry optimizing type, innovation driving type and traffic impacting type. These findings have implications for local governments and tourism management departments to achieve high-quality innovative development of cultural tourism. [ABSTRACT FROM AUTHOR]

The changing population age structure has a significant influence on the economy, society, and numerous other aspects of a country. This paper has innovatively applied the method of compositional data forecasting for the prediction of population age changes of the young (aged 0–14), the middle-aged (aged 15–64), and the elderly (aged older than 65) in China, India, and Vietnam by 2030 based on data from 1960 to 2016. To select the best-suited forecasting model, an array of data transformation approaches and forecasting models have been extensively employed, and a large number of comparisons have been made between the aforementioned methods. The best-suited model for each country is identified considering the root mean squared error and mean absolute percent error values from the compositional data. As noted in this study, first and foremost, it is predicted that by the year 2030, China will witness the disappearance of population dividend and get mired in an aging problem far more severe than that of India or Vietnam. Second, Vietnam’s trend of change in population age structure resembles that of China, but the country will sustain its good health as a whole. Finally, the working population of India demonstrates a strong rising trend, indicating that the age structure of the Indian population still remains relatively “young”. Meanwhile, the continuous rise in the proportion of elderly population and the gradual leveling off growth of the young population have nevertheless become serious problems in the world. The present paper attempts to offer crucial insights into the Asian population size, labor market and urbanization, and, moreover, provides suggestions for a sustainable global demographic development. [ABSTRACT FROM AUTHOR]

Complexity modelling of economic efficiency and growth potential is increasingly essential for countries and provinces. Evaluating the monetary flows, kinetic energy (efficiency) and potential capacity (resilience) provides crucial information for economic development. In the paper, the authors analyze growth opportunities for the Chinese economy from a system science point of view, using the perspective of information entropy, based on the input-output tables. Over the past four decades of reform and opening-up, China has made remarkable progress in its economic development. In 2007, China's GDP was at its fastest pace in history at 14.2% growth. However, after the financial crisis in 2008, the global economy experienced a downward trend and China's economic development also settled on a medium-low level of development. The traditional perspective is to rank regional development only based on GDP growth, whereas here, the authors advocate another evaluation method based on efficiency and potential growth. Unbalanced regional economic development has become problematic and has become a barrier for sustainability of China's economy. The results of the research indicate firstly that China's regional development in 2007 and 2012 has been unequal between the provinces. Secondly, the authors found that Shandong province had significantly higher indicators for efficiency and potential growth than others in the same circumstances. Authors observe that provinces tend to carry out industrial policies and adjust the structure of industry on a local level. This analysis demonstrates that the spatial imbalance of efficiency and potential of economic development under the perspective of provincial-level regions. From the perspective of industry, it indicates that the supply chain is too short, mainly focusing on the mining and processing of resources and minerals in the original upstream industry chain, while the downstream is not fully utilized. These represent some unique insights yielded through this type of analysis that authors advocate applying more broadly. [ABSTRACT FROM AUTHOR]

There is few significant attempt to integrate environmental regulation, government financial support, and corporate technological innovation in a methodological framework. Employing the data of the industrial enterprises with an annual turnover of over 20 million yuan from 30 Chinese provinces or municipalities between 2008 and 2016, this paper applies the fixed effect regression model to reveal the relationships between environmental regulation, government financial support, and corporate technological innovation simultaneously. Results show that: (1) there exists a U-shaped relation between environmental regulation intensity and technological innovation of enterprises which declines first and then climbs up, and China is still at the stage of inhibition before the “inflection point”. (2) government financial support does not significantly work on technological innovation directly, but environmental regulation drives this effect to be achieved; when the value of lnER is higher than 3.69, government financial support can significantly facilitate corporate technological innovation. (3) the comparison between regional samples reveals that heterogeneity exists in the influence of environmental regulation intensity and government financial support on corporate technological innovation. The threshold value of enabling effects of environmental regulation in eastern region is higher than that of the central and western region. These results remain consistent after we experiment several robustness checks. Theory and policy implications of our work are discussed. [ABSTRACT FROM AUTHOR]

China is facing severe pressure on its water resources and water environments. Calculating the industrial water efficiency of each province is an important index for the central government to evaluate local governments. In the traditional water resources evaluation index, the industrial water use efficiency and pollutant discharge are evaluated separately. In this paper, we collected industrial input data, output data and pollutant discharge data with a four-stage data envelopment analysis to calculate China's industrial water use efficiency with and without considering pollutant discharge, and then analyzed the factors influencing the industrial water use efficiency. The results show that the eastern coastal provinces of China have the highest water use efficiency and are less affected by pollutant discharge than other provinces. The industrial water use efficiency of the central and western provinces is lower than that of the other provinces, and the industrial water use efficiency in the central provinces is greatly affected by pollutant discharge. Factor endowment, economic development level, scientific and technological progress, industrial structure, proportion of foreign investment, water consumption per 10000 yuan of value-added by industry, industrial sewage treatment capacity and educational investment have a significant influence on the industrial water use efficiency of China. We suggest that the government strengthen the construction of sewage plants and other related infrastructure in central provinces when conducting the industrial transfer of heavy polluting enterprises. [ABSTRACT FROM AUTHOR]

Understanding the causality between energy consumption, carbon emissions and economic growth is helpful for policymakers to formulate energy, environmental and economic policies. For the first time, based on nonlinear dynamics, this paper employs multispatial convergent cross mapping (CCM) to revisit the energy-carbon-economy causation for China, India and the G7 countries using both aggregate data and per capita data. The findings indicate that there are significant differences between developing countries and developed countries. A bidirectional nexus between energy consumption, carbon emissions and economic growth is found in China and India, but various causal relationships are identified in the G7 countries, including bidirectional, unidirectional and neutral nexus. The results confirm that the decoupling phenomenon is common in most G7 countries. By leveraging a variety of samples and a new approach, this study provides new evidence for policy authorities to formulate country-specific policies to obtain better environmental quality while achieving sustainable economic growth. [ABSTRACT FROM AUTHOR]

This paper combines a Granger causality test and a VAR model to investigate the relationships among oil price shocks, global economic policy uncertainty (GEPU), and China’s industrial economic growth. Based on monthly data from 2000 to 2017, we reveal that GEPU and world oil prices jointly Granger cause China's industrial economic growth; world oil prices have a positive effect on China's industrial economic growth, while GEPU has a negative effect. Further analyses investigate the asymmetry effect of oil prices and find that the negative component shows a more significant impact on China's industrial economic growth. The results are robust to different oil price and EPU proxies. [ABSTRACT FROM AUTHOR]

Based on the calculation of the inclusive financial development level of 22 provinces and 4 municipalities in China from 2004 to 2017, this paper uses the Kernel density estimation method to further analyze the evolution of the inclusive financial index. Based on the above analysis, we make empirical analysis of the impact of China's inclusive financial inclusion development index on farmers' entrepreneurship using static panel and dynamic panel estimation method. The empirical conclusions show that there are certain differences in inclusive financial inclusion development level in various provinces in China. Improving the inclusion development level of inclusive finance can better promote farmers' entrepreneurship. Urbanization level, economic openness and regional economic development level have a significant positive effect on farmers' entrepreneurship, while farmers' income and education level have a significant negative effect on farmers' entrepreneurship. It is possible to promote farmers' entrepreneurship by improving the inclusive development level of inclusive finance, combining urbanization, increasing government investment in productive fixed assets, increasing economic openness and improving regional economic development. [ABSTRACT FROM AUTHOR]

In this paper, based on the panel data of 31 provinces and cities in China from 1991 to 2016, the regional development efficiency matrix of high-end talent is obtained by DEA method, and the matrix is converted into a continuous change of complex networks through the construction of sliding window. Using a series of continuous changes in the complex network topology statistics, the characteristics of regional high-end talent development efficiency system are analyzed. And the results show that the average development efficiency of high-end talent in the western region is at a low level. After 2005, the national regional high-end talent development efficiency network has both short-range relevance and long-range relevance in the evolution process. The central region plays an important intermediary role in the national regional high-end talent development system. And the western region has high clustering characteristics. With the implementation of the high-end talent policies with regional characteristics by different provinces and cities, the relevance of high-end talent development efficiency in various provinces and cities presents a weakening trend, and the geographical characteristics of high-end talent are more and more obvious. [ABSTRACT FROM AUTHOR]

Coal mining is one of the core industries that contribute to the economic development of a country but deteriorate the environment. Being the primary source of energy, coal has become essential to meet the energy demand of a country. It is excavated by both opencast and underground mining methods and affects the environment, especially hydrological cycle, by discharging huge amounts of mine water. Natural hydrological processes have been well known to be vulnerable to human activities, especially large scale mining activities, which inevitably generate surface cracks and subsidence. It is therefore valuable to assess the impact of mining on river runoff for the sustainable development of regional economy. In this paper, the impact of coal mining on river runoff is assessed in one of the national key coal mining sites, Gujiao mining area, Shanxi Province, China. The characteristics of water cycle are described, the similarities and differences of runoff formation are analyzed in both coal mining and pre-mining periods. The integrated distributed hydrological model named MIKE SHE is employed to simulate and evaluate the influence of coal mining on river runoff. The study shows that mining one ton of raw coal leads to the reduction of river runoff by 2.87 m3 between 1981 and 2008, of which the surface runoff decreases by 0.24 m3 and the baseflow by 2.63 m3. The reduction degree of river runoff for mining one ton of raw coal shows an increasing trend over years. The current study also reveals that large scale coal mining initiates the formation of surface cracks and subsidence, which intercepts overland flow and enhances precipitation infiltration. Together with mine drainage, the natural hydrological processes and the stream flows have been altered and the river run off has been greatly reduced. [ABSTRACT FROM AUTHOR]

Today, China is facing a very serious issue of Air Pollution due to its dreadful impact on the human health as well as the environment. The urban cities in China are the most affected due to their rapid industrial and economic growth. Therefore, it is of extreme importance to come up with new, better and more reliable forecasting models to accurately predict the air quality. This paper selected Beijing, Tianjin and Shijiazhuang as three cities from the Jingjinji Region for the study to come up with a new model of collaborative forecasting using Support Vector Regression (SVR) for Urban Air Quality Index (AQI) prediction in China. The present study is aimed to improve the forecasting results by minimizing the prediction error of present machine learning algorithms by taking into account multiple city multi-dimensional air quality information and weather conditions as input. The results show that there is a decrease in MAPE in case of multiple city multi-dimensional regression when there is a strong interaction and correlation of the air quality characteristic attributes with AQI. Also, the geographical location is found to play a significant role in Beijing, Tianjin and Shijiazhuang AQI prediction. [ABSTRACT FROM AUTHOR]

Since the economic transition, manufacturing in China has undergone profound changes not only in number of enterprises, but also in ownership structure and intra-urban spatial distribution. Investigating the changing manufacturing landscape from the perspective of ownership structure is critical to a deep understanding of the changing role of market and government in re-shaping manufacturing location behavior. Through a case study of Wuxi, a city experiencing comprehensive ownership reform, this paper presents a detailed analysis of the intra-urban spatial shift of manufacturing, identifies the location discrepancies, and examines the underlying forces responsible for the geographical differentiations. Through zone- and district-based analysis, a distinctive trend of decentralization and suburbanization, as well as an uneven distribution of manufacturing, is unveiled. The results of Location Quotient analysis show that the distribution of manufacturing by ownership exhibits distinctive spatial patterns, which is characterized by a historically-based, market-led, and institutionally-created spatial variation. By employing Hot Spot analysis, the role of development zones in attracting manufacturing enterprises of different ownerships is established. Overall, the location behavior of the diversified manufacturing has been increasingly based on the forces of market since the land marketization began. A proactive role played by local governments has also guided the enterprise location decision through spatial planning and regulatory policies. [ABSTRACT FROM AUTHOR]

This paper investigates the potential causal relationship(s) between China’s urbanization and income inequality since the start of the economic reform. Based on the economic theory of urbanization and income distribution, we analyze the annual time series of China’s urbanization rate and Gini index from 1978 to 2014. The results show that urbanization has an immediate alleviating effect on income inequality, as indicated by the negative relationship between the two time series at the same year (lag = 0). However, urbanization also seems to have a lagged aggravating effect on income inequality, as indicated by positive relationship between urbanization and the Gini index series at lag 1. Although the link between urbanization and income inequality is not surprising, the lagged aggravating effect of urbanization on the Gini index challenges the popular belief that urbanization in post-reform China generally helps reduce income inequality. At deeper levels, our results suggest an urgent need to focus on the social dimension of urbanization as China transitions to the next stage of modernization. Comprehensive social reforms must be prioritized to avoid a long-term economic dichotomy and permanent social segregation. [ABSTRACT FROM AUTHOR]