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Carbon emission issues are becoming increasingly severe, and the carbon emissions in shrinking cities, primarily characterized by population loss, are often overlooked and insufficiently studied. This paper focuses on the carbon emissions from county-level administrative units in China's three northeastern provinces from 2001 to 2017. The study scientifically identified shrinking cities and measured the differences in carbon emission characteristics between growing and shrinking cities using the Theil index. Ultimately, the paper constructs a panel spatial econometric model to analyze the factors influencing them and explore their spatial effects. (1) The total carbon emissions in the Three Northeastern Provinces exhibited an inverted U-shaped trend, increasing from 734.21 million tons in 2001 to 1731.73 million tons in 2017, with the Mann–Kendall trend test showing a significant increase; spatially, this manifests as a significant positive spatial autocorrelation. (2) The region has 138 shrinking cities, accounting for over 50%; regarding carbon emission characteristics, the Theil index has consistently remained above 0.18, indicating significant differences between the carbon emissions of growing and shrinking cities. (3) The panel spatial econometric model results show that the influencing factors of carbon emissions in shrinking cities have unique directions, intensities, and spatial effects. In shrinking cities, aside from localized GDP effects and per-capita GDP acting as a suppressant, the population size has a pronounced inhibitory effect on local and surrounding carbon emissions. The analysis reveals significant differences in the carbon emission patterns and mechanisms between growing and shrinking cities; based on these results, the paper proposes differentiated carbon control strategies. [ABSTRACT FROM AUTHOR]

China’s paper industry consumes a lot of energy and emits huge amounts of pollutions. The Chinese government over the past decades has done a lot to promote energy efficiency of the industry. This paper studies the impact of industrial polices to improve energy efficiency. The energy efficiency change is firstly studied under a framework of total factor efficiency. On this basis, different econometric models are built to discuss the detailed energy efficiency characteristics of the paper industry. The main results are as follow: (i) ownership structure did influence the energy efficiency, but the influence is different in different conditions; (ii) energy efficiency of the paper industry can be improved by economies of scale; (iii) market competition can to some extent overcome the motivation and supervision problem that often occur in state-owned companies; (iv) energy price cannot play the role of resource allocation well in China. Finally, based on our findings, some suggestions are provided. [ABSTRACT FROM AUTHOR]

The digital economy has great potential to sustain China's high-quality economic growth and substantially strengthen urban innovation capacity. This paper developed a digital economy index using city-level data from China and measured the level of urban innovation with patents per capita. We used a spatial econometric model to explore the spatial implications of the digital economy on urban innovation, probed into the mechanism by which the digital economy affects urban innovation, and further measured the spatial spillover distance and threshold of the digital economy on urban innovation. The findings suggest that China's digital economy and urban innovation are characterized by spatial aggregation, and the spatial distribution varies from region to region. The digital economy, with strong spatial spillover effects on the innovation capacity of cities in China, may not only enhance the innovation capacity of one city but also drive a simultaneous growth of the innovation capacity in peripheral cities. The analysis of mechanisms indicates that the digital economy enhances local innovation capacity directly through promoting human resources and increasing science and technology spending and drives the improvement of the innovation capacity in peripheral cities through the spatial spillover of human resources and science and technology spending. The effects of the latter one outweigh those of the former one. The analysis of heterogeneity shows that the central, western, and northern regions, where the digital economy is relatively less developed, have the latecomer advantage, and the digital economy has more prominent effects on innovation capacity. Calculating the spillover distance and threshold demonstrates that the digital economy influences urban innovation within a spatial spillover range and threshold of approximately 500 kilometers. Within 500 kilometers, the positive spatial spillover effects prevail, while beyond 500 kilometers, the negative siphon effect prevails. Therefore, it is necessary to consider the differences in the impact and role of the digital economy on urban innovation from a spatial perspective. [ABSTRACT FROM AUTHOR]

This paper employs a unique data set to analyze the trading behavior of wealthy individual investors across Mainland China and their impact on Chinese stock markets' tail risk. Results show that the wealthy individual investors' trading behavior can explain Chinese stock markets' tail risk, and the daily investment portfolios based on the network density of wealthy individual investors have significant excess returns. This paper also investigates the determinants of wealthy individual investors' trading behavior with the social network method and the spatial econometric model, and reveals that wealthy individuals benefit from the spillover effect of their trading behavior through the investor networks. The results of this paper not only reveal micro evidence for the formation mechanism of asset prices, but also provide insight into the behavior of wealthy individual investors. [ABSTRACT FROM AUTHOR]

In the field of risk assessment, the traditional econometric models are generally used to assess credit risk. And with the introduction of the "dual-carbon" goals to promote the development of a low-carbon economy, the scale of green credit in China has rapidly expanded. But with the advent of the big data era, due to the poor interpretability of a traditional single machine learning model, it is difficult to capture nonlinear relationships, and there are shortcomings in prediction accuracy and robustness. This paper selects the adjusted ensemble learning model based on the homogeneous and heterogeneous factors for user default prediction, which can efficiently process large quantities of high-dimensional data. This article adjusts each model to adapt to the task and innovatively compares various models. In this paper, the missing value filling method, feature selection, and ensemble model are studied and discussed, and the optimal ensemble model is obtained. When comparing the predictions of single models and ensemble models, the accuracy, sensitivity, specificity, F1-Score, Kappa, and MCC of Categorical Features Gradient Boosting (CatBoost) and Random undersampling Boosting (RUSBoost) all reach 100%. The experimental results prove that the algorithm based on adjusted homogeneous and heterogeneous ensemble learning can predict the user default efficiently and accurately. This paper also provides some references for establishing a risk assessment index system. [ABSTRACT FROM AUTHOR]

Digital economy has become a "new engine" that driving global economic growth. Nevertheless, numerous controversies persist regarding whether and how digital economy can facilitate the development of emerging industries. Thus, this paper investigates how digital economy affects creative industries development in China and whether innovation efficiency mediates this relationship. Drawing upon a panel data set containing 29 Chinese provinces from 2012 to 2019, an econometric model is constructed for empirical analysis. We find that digital economy significantly promotes creative industries development, and innovation efficiency plays a partial mediating role between digital economy and creative industries development. According to the influence mechanism, the digital economy of various regions could promote the creative industries development by improving the innovation efficiency. Finally, relevant suggestions were put forward from the expanding application paths, improving regional innovation efficiency, and creating an innovative environment. [ABSTRACT FROM AUTHOR]

The development of the Internet has changed many traditional commercial models of enterprises. Therefore, the term Internet development is increasingly drawing attention from scholars. However, we are not certain whether the development of the Internet improves the problem of difficult financing of enterprises and enhances enterprise financing efficiency. This paper analyzes whether Internet development can promote enterprise financing efficiency. First, the Data Envelopment Analysis- Slack Based Measure (DEA-SBM) model is applied to measure the enterprise financing efficiency values of 31 provinces in China. The measurement results indicate that the enterprise financing efficiency in the eastern regions is higher than that of central and western regions. Then, this paper further tests if Internet development can contribute to enterprise financing efficiency based on an econometric model. The analysis results indicate that Internet development has an obvious promoting effect on enterprise financing efficiency. Later, spatial econometric models are adopted in this paper to further analyze if Internet development has a spatial overflow effect on enterprise financing efficiency. The results indicate that Internet development indeed has a spatial overflow effect on enterprise financing efficiency. [ABSTRACT FROM AUTHOR]

Climate change has become a critical global issue and challenge, with significant implications for financial enterprises as an integral part of economic activities. A thorough analysis of the impact of climate change on the high-quality development of financial enterprises is of great importance for financial sustainability. This paper first conducts an indepth mathematical analysis of the intrinsic mechanisms through which climate change affects the high-quality development of financial enterprises by establishing a game theory model. Secondly, using data from listed companies for the years 2000-2020, an econometric model is constructed to empirically examine the relationship between climate change and the high-quality development of financial enterprises. The research findings demonstrate that climate change significantly inhibits the highquality development of financial enterprises, as evidenced by robust results obtained through various methods such as data truncation, variable substitution, and changes in sample periods. Furthermore, this study addresses the endogeneity of the regression model using propensity score matching (PSM), instrumental variable methods, and system generalized method of moments (GMM). Additionally, climate change impacts the high-quality development of financial enterprises through technological innovation. Given the backdrop of climate change, understanding the relationship and logic between climate change and the high-quality development of financial enterprises and discerning the channels and mechanisms through which climate change affects their development are crucial. This research provides a new perspective and expands the research frontier on the high-quality development of financial enterprises, enriching the theoretical foundations in this field. [ABSTRACT FROM AUTHOR]

Urban agglomeration plays a vital role in fostering high-quality and sustainable development in China, where urbanization rates significantly influence both urban and rural environments, generating different economic and socio-spatial impacts that, in turn, influence carbon emissions in cities. To delve into the influencing mechanisms of carbon emissions, this paper examines the spatio-temporal pattern of carbon emissions across 41 cities in the Yangtze River Delta urban agglomeration in China. It utilizes data on economic, social, and spatial factors from 2012 to 2019 and employs a spatial econometric regression model for analysis. The results indicate that carbon emissions of cities in the urban agglomeration exhibited strong spatial correlation from 2012 to 2019, characterized by relatively stable cold and hot spots, along with continuous outward spread of high-value zones. Economic and social factors demonstrate a significant positive spatial correlation with carbon emissions of a city, with weak spatial spillover effects. Spatial factors exhibit correlations with carbon emissions in both the city and neighboring cities, with strong spatial spillover effects. Moreover, the spatial layout and functional division of cities in the urban agglomeration also significantly impact the spatio-temporal pattern of carbon emissions. [ABSTRACT FROM AUTHOR]

Financial elements and R&D elements are significant drivers for enhancing regional innovation efficiency. This paper measures financial elements by financial development scale and the marketization level of the financial industry and R&D elements by the inputs and flow of R&D personnel and R&D capital and specifically considers R&D element flow to quantify the consequential spatial spillover effects. Based on provincial panel data from 2008 to 2018, the paper firstly estimates the regional innovation efficiency of China's 30 provincial-level administrative regions using super-efficiency DEA and then conducts an empirical analysis of the influence of financial elements and R&D elements on regional innovation efficiency by the use of the Tobit model and three spatial econometric models. It is found that, by and large, the financial development scale, the marketization level of the financial industry, the inputs of R&D personnel and R&D capital, and R&D capital flow all have significant effects on regional innovation efficiency. Nonetheless, by region, R&D personnel flow in central China can significantly boost regional innovation efficiency while fails in eastern and western China. From the spatial perspective, both financial elements and R&D elements have significant positive spatial spillover effects. Therefore, in order to bolster regional innovation efficiency, it is crucial to improve the allocation of financial elements and R&D elements and build a tight regional collaborative innovation network. [ABSTRACT FROM AUTHOR]

Watershed ecological compensation is an important means to protect the ecological environment and an important part of China's ecological civilization construction. It can promote the sustainable and coordinated development of a region, enhance the advantages of the ecological environment in the upstream area, and lay the foundation for the high-quality development of ecological tourism in the upstream area. The accurate evaluation of the effect and efficiency of ecological compensation is a prerequisite for optimizing and perfecting the ecological compensation system. In order to evaluate the effect and efficiency of watershed ecological compensation, this paper used the case study area of Anyuan County, an important ecological area of the Dongjiangyuan watershed in the pilot area of China's interprovincial watershed ecological compensation. This paper established an evaluation index system, used the entropy method and the data envelopment analysis (DEA) method to construct a watershed ecological compensation effect and efficiency evaluation model, and selected the ecological compensation index data from 2015 to 2020 to evaluate the effect and efficiency. This paper also constructed an econometric model to analyze their driving factors. The results showed that the effect of watershed ecological compensation was generally on the rise. Low pure technical efficiency (PTE) was the main reason for low comprehensive efficiency (CE), and the management efficiency of ecological compensation projects needs to be improved. The overall performance of scale efficiency (SE) was good, but there was still a problem of capital redundancy. Ecological compensation expenditure had a significant negative impact on the efficiency of ecological compensation, and ecotourism had a significant positive impact on the effect and efficiency of the ecological compensation. The results of this study can provide a scientific basis and theoretical reference for improving the effect and efficiency of watershed ecological compensation schemes. [ABSTRACT FROM AUTHOR]

Sustainable development can be mainly achieved by promoting the green transformation and development of the world economy and by improving the efficiency of regional green development, which often receive extensive attention from the academia. This paper uses a spatial econometric model to estimate the impact of manufacturing agglomeration on green development efficiency based on the panel data of China's Yangtze River Economic Belt (YREB). The results show an overall large gap of green development efficiency between regions in the Yangtze River Economic Zone, mostly due to the extremely uneven development of green development efficiency in the upper reaches. Opposite to the middle and lower reaches, manufacturing agglomeration in the upper reaches of the YREB improves green development efficiency. Manufacturing agglomeration is conducive to the improvement of green development efficiency in adjacent areas. Nonetheless, it may hinder green development efficiency by inhibiting green technological innovation. This paper provides empirical evidence and policy implications for applying manufacturing agglomeration to promote green development efficiency in accordance with local conditions. [ABSTRACT FROM AUTHOR]

In the context of carbon neutralization and carbon peak, carbon reduction in key industries has become a central topic in our country. As an important part of technological progress, it is necessary to study the effect of technology import on carbon emission reduction in key industries. Based on the panel data of 30 provinces. from 2011 to 2020, this paper used the fixed-effect model to analyze the emission reduction effect in key industries on the development status of technology import. The spatial econometric model was used to analyze the spatial characteristics of carbon emissions of technology import and key industries. Then, the mediating effect model was used to bring industrial technological innovations into the research category to analyze the mediating role of technology imports on the carbon emissions of key industries. Finally, a robustness test proved the reliability of the model. The findings were as follows: (1) Technology import significantly promoted carbon emission reduction in key industries; (2) In terms of the spatial relationship, technology import and carbon dioxide emissions had significant spillover effects, and there were trends of high and high aggregation and low and low aggregation, with the impact of technology import on carbon dioxide emissions having a siphon effect; (3) Industrial technological innovation played an intermediary role in this path, but it was a negative role, which was not, in general, conducive to the reduction of carbon emissions of key industries. On this basis, the paper puts forward several policy suggestions. [ABSTRACT FROM AUTHOR]

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Scientifically measuring the level of environmental governance (EGL) and understanding its spatial convergence has important reference value for ecological governance. In this paper, the global entropy method is applied to measure the EGL of 284 prefecture-level cities in China from 2007 to 2019, which are divided into three major river basins, including the Yellow River, Yangtze River, and Pearl River, to observe the spatial–temporal evolutionary characterization through a standard deviation ellipse model. The coefficient of variation and the spatial econometric model are the tools used to conduct the spatial convergence test. The results are as follows: (1) China's EGL is low overall, though it is fluctuating upward at low magnitude, and the three major river basins follow the ranking: The Pearl River Basin > The Yangtze River Basin > The Yellow River Basin. (2) Spatially, the distribution pattern of China's EGL changes from "scattered and sporadic" to "multipolar core". (3) The center of China's environmental governance was concentrated in the east from 2007 to 2019, and the EGL in the midstream and downstream regions of the three major river basins increased rapidly. (4) Environmental governance in China has significant absolute and conditional β-convergence characteristics, as do the three major basins, while the ranking of convergence speed remains "Yangtze River Basin > Yellow River Basin > Pearl River Basin". Of these, economic development accelerated the convergence rate of environmental governance in China and its three major river basins; financial pressure significantly inhibited the convergence of the EGL of the Yellow River Basin. The improvement of the EGL in the Pearl River Basin was also negatively influenced by the industrial structure. [ABSTRACT FROM AUTHOR]

To support the 2021 Manufacturing & Service Operations Management (M&SOM) Data-Driven Research Challenge, RiRiShun Logistics (a Haier group subsidiary focusing on logistics service for home appliances) provides MSOM members with logistics operational-level data for data-driven research. This paper provides a detailed description of the data associated with over 14 million orders from 149 clients (the consigners) associated with 4.2 million end consumers (the recipients and end users of the appliances) in China, involving 18,000 stock keeping units operated at 103 warehouses. Researchers are welcomed to develop econometric models, data-driven optimization techniques, analytical models, and algorithm designs by using this data set to address questions suggested by company managers. History: This paper has been accepted as part of the 2021 M&SOM Data-Driven Research Challenge. Funding: This work was supported by the National Natural Science Foundation of China [Grants 72091215/72091210, 71871207, 71991464/71991460, and 71921001]. Supplemental Material: Data and the online appendix are is available at https://doi.org/10.1287/msom.2021.0994. [ABSTRACT FROM AUTHOR]

The digital economy is crucial to promoting green technology innovation and development. However, there needs to be more research on the relationship between the digital economy, digital talent aggregation (DTA), and green technology innovation (GTI). Therefore, based on the data from 30 provinces, municipalities, and autonomous regions in mainland China (excluding Tibet) from 2011 to 2020, this paper uses fixed effect, threshold effect, moderating effect model, and spatial econometric model to make an empirical analysis of this research direction. The results show that (1) there is a nonlinear relationship between the digital economy and green technology innovation (GTI). This effect has regional heterogeneity effects. In the central and western regions, the digital economy is more prominent in promoting green technology innovation (GTI). (2) Digital talent aggregation (DTA) has a negative moderating effect on the influence of the digital economy on promoting green technology innovation (GTI). (3) The negative spillover effect of the digital economy on local green technology innovation (GTI) will be intensified at the spatial level due to the accumulation of digital talents. Therefore, this paper suggests that the government should actively and reasonably develop the digital economy to promote green technology innovation (GTI). In addition, the government can implement a flexible talent introduction policy, strengthen talent quality education and talent service station construction. [ABSTRACT FROM AUTHOR]

This paper investigates how digital finance alleviates the resource curse effect from resource-based cities in China. This paper selects the data from 88 resource-based cities in China from 2011 to 2019 to construct the econometric model test hypothesis. The results show that (1) a resource curse does exist in Chinese resource-based cities. (2) Digital finance can alleviate the resource curse of resource-based cities in China, and this effect has two significant thresholds. (3) The heterogeneity test results show that digital finance's mitigation effect on the resource curse significantly differs in cities with different environmental regulation intensities and resource abundance. (4) Using the implementation of the broadband China strategy as the proxy variable of digital finance for the robustness test, the above conclusions are still robust. This paper considers the impact of digital upgrading on the financial industry and further studies the mitigation effect of digital finance on the resource curse. It provides a new perspective to study the recent changes in traditional issues in the digital era. [ABSTRACT FROM AUTHOR]

This paper aims to the debate on the nexus between informal economies and the environment by investigating the long-term dynamic impacts of China's informal economies on pollution and considering regional differences in informal economies' pollution. This paper uses the Multiple Indicators Multiple Causes (MIMIC) model to estimate the size of informal economies and employs econometric models to examine their relationships to pollution based on provincial-level panel data from 2000 to 2017. The results indicate that informal economies' effects on environmental pollution are not purely positive or negative. Rather, our model indicates that there is an inverted U-shaped relationship between informal economies and pollution in the long run in China; this means that the level of environmental pollution increases at first and then decreases with the growth of informal economies. Further analysis shows that while this inverted, U-shaped relationship is significant in different regions of China, it is affected by different environmental impact factors. The paper concludes by discussing the policy implications for environmental protection and sustainable development. [ABSTRACT FROM AUTHOR]

The management of international students has become a new challenge that China and most countries in the world must face in the context of the "Belt and Road Initiative" (BRI) and the globalization of higher education. In this paper, we conducted an empirical study on international students in China (ISC) based on a combination of spatial econometric models and analytical methods such as BCG, GeoDetector, and DDCAM, trying to provide a basis for "evidence-based decision-making" by the government in the management of international students and talents. Quantitative analyses revealed significant diversity and spatial effects in the spatio-temporal dynamics of ISCs, with the emergence of star, gazelle, cow, and dog types, suggesting that the scientific management of ISCs requires both local adaptation (spatial differentiation and heterogeneity) and regional collaboration (spatial correlation and autocorrelation). There were many factors affecting the spatio-temporal dynamics of ISCs, and the force of different factors varied considerably, with the key factor more than 0.5 but the auxiliary factor being less than 0.2. Moreover, the factors had significant interaction effects, and a large number of super-interacting factor pairs emerged, with a joint force of more than 0.9, twice the force of a single factor. Generally, the factors had a complex driving mechanism, suggesting that ISC management requires identifying the key and important factors, while attaching emphasis to the synergistic effects among different factors. The recommendation is that China should manage ISCs in spatial zones and introduce differentiated development strategies and policies in different zones. In conclusion, this paper proposes a technical route integrating "dynamic analysis-driving mechanism-policy design" for international students, which is applicable to China, while providing a reference for the management and spatial planning design of international students in other countries in the world. [ABSTRACT FROM AUTHOR]

Whether digital finance should be included in the quantitative framework of monetary policy in emerging market countries has been widely discussed by scholars. However, the current research just focused on a single format of digital finance, lacking comprehensive analysis at the overall level and the refinement of general rules. Therefore, this paper constructed a spatial econometric model to empirically analyze the impact of digital finance on the effectiveness of monetary policy and its heterogeneity, taking China as the representative of emerging market countries. The empirical test showed that (1) Although the total index of digital finance had a negative impact on economic growth, the interaction between digital finance and monetary policy was significantly positive. This indicated that the "moderating effect" of monetary policy was beneficial to digital finance in promoting economic growth, which was confirmed from the subindexes level as well. (2) The development of digital finance had obvious characteristics of the "polarization effect" and the "spatial spillover effect". Meanwhile, there was a significant regional difference in the "moderating effect" of monetary policy. (3) In terms of control variables, consumption level, fixed capital formation level, and fiscal policy all had a significant positive impact on economic growth, with a positive "spatial spillover effect". Whereas, the impacts of COVID-19 and export level on economic growth were both negative. Hence, coping with the challenges of COVID-19 and revitalizing exports were important breakthroughs for emerging market countries to recover the domestic economy. Finally, based on the empirical conclusions, this paper proposed three suggestions. First, monetary policy should be strengthened to intervene in the development of digital finance. Second, digital financial development should be integrated into the quantitative framework of monetary policy. Third, it is essential to build a "double pillar" policy framework to compensate for the shortage of monetary policy. [ABSTRACT FROM AUTHOR]

The impact of Chinese-style fiscal decentralization on regional energy intensity has long been disputed by the supporters of "federal environmentalism" and those who hold "race to the bottom" views. At the same time, with the transformation of China's development mode, the Chinese government is paying increasing attention to the protection of ecological civilization and the realization of sustainable development, and the government's attention to the ecological environment is becoming an important factor affecting regional energy intensity. Therefore, this paper takes the fiscal decentralization and ecological attention of local governments in China as the research object and analyzes their impact mechanism on regional energy intensity. Firstly, the entropy weight method was used to measure the comprehensive score of fiscal decentralization of Chinese local governments, and the text analysis method was used to obtain the ecological attention index of Chinese provincial local governments, which was sorted into panel data of 30 provinces (municipalities and autonomous regions) in mainland China from 2007 to 2019. The spatial econometric model and panel threshold model are structured as the means for analyzing the impact that fiscal decentralization and the ecological attention of local governments have, respectively, on regional energy intensity targets. We obtained the following conclusions: Chinese fiscal decentralization can significantly improve the regional energy intensity, and the fiscal decentralization of a region can significantly reduce the energy intensity in nearby regions; the enhancement of ecological attention of local governments will significantly inhibit regional energy intensity, and also has a significant inhibitory effect on the energy intensity of neighboring regions. As the threshold variable—which is the ecological attention of local governments—increases and reaches a certain level, fiscal decentralization will significantly and reversely inhibit regional energy intensity, indicating that the ecological attention of local governments can moderate the distortion of fiscal decentralization with regards to regional energy efficiency. [ABSTRACT FROM AUTHOR]

Purpose: Drawing on social network and information diffusion theories, the authors study the impact of the structural characteristics of a seller's local social network on her promotion effectiveness in social commerce. Design/methodology/approach: The authors define a local social network as one formed by a focal seller, her directly connected users and all links among these users. Using data from a large social commerce website in China, the authors build econometric models to investigate how the density, grouping and centralization of local social networks affect the number of likes received by products posted by sellers. Findings: Local social networks with low density, grouping and centralization are associated with more likes on sellers' posted products. The negative effects of grouping and centralization are reduced when density is high. Originality/value: The paper deepens the understanding of the determinants of social commerce success from a network structure perspective. In particular, it draws attention to the role of sellers' local social networks, forming a foundation for future research on social commerce. [ABSTRACT FROM AUTHOR]

This paper addresses the substitution elasticity of capital on the labour force in the context of the development of intellectualization. Given the substitution of capital for labour, China's benchmark listed logistics companies are compared with an American company to discuss the evolution of capital – labour substitution. A large-scale intellectualization process began in 2017, and based on a variable elasticity of substitution, this paper creates an econometric model of substitution elasticity between capital and labour and its evolution between 2017 and 2021. The American logistics company UPS maintains a relatively high level of substitution elasticity, and Chinese logistics companies are quickly catching up. The substitution elasticity of capital on labour in Chinese enterprises trends upward year after year. In 2021, the capital – labour substitution elasticity of logistics enterprises in both countries showed considerable growth. The calculation model of substitution elasticity presented in this paper can be extended to different regions and industries to measure intelligent development levels and the relationship between capital and the labour force. [ABSTRACT FROM AUTHOR]

Based on provincial data pertaining to China from 2003 to 2018, this paper empirically analyzes the impact of the industrial structure on haze pollution by constructing static and dynamic spatial econometric models. The marginal contribution of this paper lies in the analysis based on two indicators: the upgrading and rationalization of the industrial structure. The results indicate that: at the overall level, haze pollution in China exhibits a significant positive spatial correlation and remains relatively stable, upgrading and rationalization of the industrial structure can significantly reduce haze pollution, the control variables of technological progress and trade openness yield obvious haze reduction effects, and the market-oriented haze reduction effect is better that of the government behavior. In terms of the robustness, the effect of industrial structure upgrading is not obvious in the eastern regions and even aggravates haze pollution in the central and western regions, while industrial structure rationalization can play a role in haze reduction in all regions. Industrial structure upgrading and rationalization achieve better effects in the southern region but can aggravate haze pollution in the northern region. Based on the results of the time period test, the effect is very obvious at the first stage but not that at the second stage because of the diminishing marginal effect. The robustness results of the replacement of the core variables and dynamic spatial Durbin model further validate the empirical results in this paper. Finally, according to the empirical results, we propose corresponding policy implications. [ABSTRACT FROM AUTHOR]

The adjustment of green finance and energy structure is gradually becoming a new engine that reduces environmental pollution in China. In this paper, the energy structure is introduced in the process of discussing the impact of green finance on environmental pollution. We analyze the spatial correlation of green finance and study whether the adjustment of energy structure is affected by green finance and thus affects environmental pollution using a spatial econometric model. The results of empirical analysis show that green finance among provinces presents a significant spatial agglomeration, improving the green finance, and the energy structure can significantly reduce environmental pollution, and there are significant spatial spillover effects. There is inverted U-shaped relationship between energy structure and green finance in the national space, that is, after the green finance is raised to a certain extent, with the level of green finance once more, the energy structure will gradually improve, and then, green finance drives the reduction of environmental pollution by improving the energy structure. The results of the heterogeneity analysis show that compared with other regions, the improvement of the green finance in the eastern region has significantly improved the energy structure, and environmental pollution has also decreased every year. [ABSTRACT FROM AUTHOR]

This paper redefines the connotation of China's human development in the context of the new development concept and high-quality development, and constructs the China Human Development Index (CHDI) indicator system accordingly. Then, based on the inequality adjustment model and DFA model, the human development level of each region in China from 1990 to 2018 is measured, and the spatial and temporal evolution characteristics of China's CHDI and the current situation of regional imbalance are analyzed accordingly. Finally, LMDI decomposition technique and spatial econometric model were used to study the influencing factors of China's human development index. The results show that: (1) The weights of the CHDI sub-index estimated by the DFA model have good stability, and it is a relatively good objective weighting method. (2) Compared with the HDI, the CHDI in this paper can better reflect the level of human development in China. (3) China's human development has made great achievements and has basically achieved the leap from the low human development level group to the high human development level group. However, there are still significant gaps between regions. (4) From the results of LMDI decomposition, the livelihood index is the most important driving index of CHDI growth in each region. From the results of spatial econometric regressions, there is a strong spatial autocorrelation of China's CHDI among the 31 provinces. GDP per capita, financial education expenditure per capita, urbanization rate, and financial health expenditure per capita are the main influencing factors of CHDI. Based on the above research findings, this paper proposes a scientific and effective macroeconomic policy with important reference value for promoting the high-quality development of China's economy and society. [ABSTRACT FROM AUTHOR]

Based on the theoretical knowledge of technological innovation, this paper designs a sensor data value incubation model and a sensor data collection model to collect the original data on green innovation efficiency. In order to explore the spatial and temporal differentiation characteristics of China's provincial green innovation efficiency and the spatial spillover effect of China's provincial green innovation efficiency, the entropy weight TOPSIS model is adopted to measure the green innovation efficiency of China's 30 provinces (cities) from 2005 to 2021 and analyze its temporal and spatial evolution characteristics. This paper uses an exploratory spatial data analysis method to prove the agglomeration phenomenon of China's provincial green innovation efficiency in the ground space. Finally, a spatial econometric model is introduced to study the impact of government R&D investment, green supervision, and green innovation efficiency on spatial spillover effects. The study found the following three conclusions: First, the efficiency of green innovation in China's provinces has been fluctuating in stages, and the overall trend has been increasing year by year. The overall efficiency of green innovation in China's provinces is low, and the overall development is uneven and uncoordinated. Second, from the results of the spatial autocorrelation test, there is a clear and positive spatial correlation between China's provincial green innovation efficiency and agglomeration in the geospatial space. Third, government R&D inputs and different types of green regulations have a significant impact on green innovation efficiency and have significant spatial spillover effects. Along from the eastern region to the central region, then to the northeast and western regions, the degree of effect on green innovation efficiency and the intensity of spatial spillover effects have gradually weakened. It is believed that the government should reduce R&D investment in the eastern region and increase green sewage charges. Instead, the government should raise R&D investment in the central, northeast, and western regions and offer enterprises green innovation subsidies. [ABSTRACT FROM AUTHOR]

In view of China's rapid urbanization for decades and its environmental effects, this paper focused on the impact of urbanization on fine particulate matter (PM2.5) concentration, and estimated the definitive urbanized population whose PM2.5 concentration reached the peak according to the comparison of classical static/dynamic spatial econometric models. The estimation results of 227 prefecture-level cities and municipalities directly under the central government covering the period 1998–2016 show that the spatial spillover effect is statistically significant, while the exogenous effect stands out in the dynamic spatial Durbin model. In terms of the relationship between urbanized population and PM2.5 concentration, the cities themselves and the exogenous influences from other neighboring cities are U-shaped and inverted U-shaped with urbanized population at the inflection point that 3.77 million and 1.77 million, respectively. Moreover, the exogenous effects occupy the mainstream position, indicating that the PM2.5 concentration of prefecture-level cities mostly comes from the input of surrounding cities. It is proven in this paper that a moderate scale of population urbanization is an important factor in haze control, which should be accompanied by joint governance and coordination of urban agglomeration. [ABSTRACT FROM AUTHOR]

Based on the panel data of 30 provinces in China from 2011 to 2020, this paper empirically examines the direct effect, spatial spillover effect, and total effect of green finance on carbon emission intensity through the spatial econometric model, considering both spatial and temporal patterns. The results show the following: (1) The carbon emission intensity of each province in China shows a noticeable spatial spillover effect and a positive spatial correlation distribution of "high-high" and "low-low" agglomeration. (2) The development of green finance in China is interrelated but uneven in space, which presents a gradient strengthening trend from the west to the east. (3) Green finance development will curb the intensity of carbon emissions, and this effect has gradually been increasing over time and differs by region. Specifically, green finance will increase the carbon emission intensity of adjacent areas in the short term but will significantly reduce the local province's carbon emission intensity to a larger extent. Finally, it puts forward policy recommendations to promote the coordinated development of green finance and a low-carbon economy. [ABSTRACT FROM AUTHOR]

The topic of air pollution and its effect on public health has become a hot policy issue that has attracted worldwide attention, but this attention has seldom been extended to the causal relationship between atmospheric environmental policy (AEP), air pollution, and public health. This paper uses panel data from 30 provinces in China to construct spatial econometric models that analyze the impact of AEP on air pollution, the impact of air pollution on public health, and the mediation effect that air pollution may have between AEP and public health. The results demonstrate that there is a significant positive spatial spillover effect of soot and dust (SD) emission intensity and the overall air pollution level as measured by the Air Pollution Index (API). The AEP has significant inhibitory effects on the intensity of sulfur dioxide and SD emissions, as well as on overall air pollution. An increase in the overall air pollution level has a significant detrimental effect on public health as measured by average life expectancy. Air pollution as measured by API is a mediating factor in the relationship between AEP and public health. The study results could help to effectively control air pollution and promote public health by leading to improvements in regional pollution prevention and control mechanisms and strengthening of the central government's policy formulation and local governments' policy implementation process. [ABSTRACT FROM AUTHOR]

Promoting the high-quality development of agriculture is an inevitable requirement toward realizing the transformation from a large agricultural country to a powerful one, and optimizing factor allocation is a prerequisite. In this paper, we use spatial econometric models to analyze the impact of factor misallocation on the high-quality development of the agricultural economy based on panel data from 154 prefecture-level cities in major grain-producing regions from 2004 to 2020. We found that factor misallocation was relatively low at the prefecture level, with an average annual decrease of 0.82 percent, compared to an average annual increase of 1.29 percent for the high-quality development of the agricultural economy. Factor misallocation inhibited improvements in high-quality agricultural economic development in adjacent cities. This conclusion remained stable after a series of tests, and the inhibitory effect exhibited significant spatiotemporal heterogeneity due to differences in geographical location, developmental level, and factor allocation methods. At the same time, a mechanism test demonstrated a continuous weakening of the inhibitory effect, accompanied by the optimization and upgrading of the agricultural industry, as well as an improvement in agricultural scientific and technological progress. In addition, nonlinear tests demonstrated that the impact of factor misallocation on the high-quality development of the agricultural economy exhibits significant nonlinear features as agricultural science and technology advances. [ABSTRACT FROM AUTHOR]

As a provider of public goods and a corrector of externalities, the government has a significant effect on the local environment. Based on annual province-level data from 1998 to 2015, this paper decomposes the changes in sulfur dioxide emissions into end pollution control effects and source pollution control effects by a complete decomposition model. It then uses a spatial econometric model to investigate how government size expansion affects sulfur dioxide emissions. The results show that under the promotion system based on appointment, the local government size and the neighboring government size are not conducive to reducing local sulfur dioxide emissions. With the expansion of the government size, the degree of environmental degradation caused by competition among governments is more serious. In the way of influence, the impact of local government size on the sulfur dioxide emissions is mainly through restraining the effect of end pollution control. The impact of neighboring government size on the sulfur dioxide emissions is mainly through weakening the effect of source pollution control. [ABSTRACT FROM AUTHOR]

Sci-tech and finance plays an increasingly important role and have become an important driving force in economic development. In China, the problem of insufficient financial support for sci-tech innovation is important to enterprises. According to the internal relationship between different stages of Sci-tech and the finance system, this paper is aimed at exploring the efficiency measurement method between sci-tech and finance systems. Firstly the multi-stage collaborative structure of sci-tech finance is built, where the system of sci-tech is divided into three stages including the R&D stage, transformation stage of sci-tech achievements and industrialization stage, and the financing channel is the input of the finance system into the sci-tech system at different stages. The measurement method of the multi-stage collaborative efficiency between sci-tech and finance systems is put forward by the framework of network DEA. Then, taking China as an example, we collect the information of 30 provinces and cities from 2009 to 2016 and measure the efficiency of each system and the collaborative efficiency of the both. The efficiency's spatial correlation is tested by means of Moran index. Finally, the influencing factors of the collaborative efficiency are analyzed based on the spatial econometric regression model, which considers the financing channels and human capital. To sum up, there are significant differences in the sci-tech finance collaborative efficiency among regions in China. Among them, the collaborative efficiency of Beijing, Shanghai and Jiangsu ranks in the top three. Comparing the different stages of the sci-tech system, the commercialization stage is a weak link in many regions of China. Human capital and financing channels of sci-tech finance have different degrees of positive impact on the sci-tech finance collaborative efficiency. Among them, human capital plays a greater role in promoting the sci-tech finance collaborative development. [ABSTRACT FROM AUTHOR]

Accurate measurement of agricultural total factor productivity (AGTFP) is crucial to measure the level of sustainable agricultural development, and agricultural carbon sink is an important element to leverage the development of green transformation. Few studies have incorporated agricultural carbon sink into the measurement framework of AGTFP, and the evolutionary dynamics and related spatial effects of Chinese AGTFP from the perspective of carbon sinks are unclear. On this basis, the paper used a provincial-level agricultural panel data set of China from 2000 to 2019 to measure the provincial indicators of agricultural carbon sinks, CO2 emissions and agricultural non-point source pollution. Then, we incorporated these environmental factors into the measurement framework of AGTFP and used the SBM-DEA model to calculate the Chinese AGTFP from the perspective of carbon sinks. We further analyzed the spatial and temporal divergence and convergence of AGTFP in China using Moran'I and spatial econometric models. We found that after measuring AGTFP, including agricultural carbon sinks, 28 out of 30 Chinese provinces showed an increased trend, but the development gap between regions was obvious. The spatial econometric model showed a significantly positive spatial correlation between the AGTFP of each province and did not have absolute α-convergence and absolute β-convergence characteristics. After adding the control variables of resource endowment of each province, it showed conditional β-convergence characteristics, and the spatial spillover effect of China's AGTFP was increasing. Finally, the paper proposed policy recommendations for the sustainable and coordinated development of China's agricultural regions in response to the research findings. [ABSTRACT FROM AUTHOR]

The increasing carbon emissions have been a major concern for most countries around the world. And as a result, every country is concerned about developing appropriate strategies to curtail it. As a major economy and the largest carbon emitter in the world, China has pledged to reduce the carbon intensity by 60–65% by 2030, compared with 2005 levels, and achieve carbon neutrality before 2060. Therefore, the analysis of the impact of China's carbon intensity is becoming an increasing important topic. Due to the spatial heterogeneity of carbon intensity, various spatial econometric models have been applied in this field. However, the existing literatures failed to consider the cross-products of relevant factors. This paper constructs our dynamic general nesting spatial panel model (GNS) with common factors to deal with the dilemma, and examines the direct and spatial–temporal spillover effects of industrial structure, GDP per capita, investment in anti-pollution projects as percentage of GDP and energy price on carbon intensity in China over the period 2003–2017. Our analysis shows that: (1) China's carbon intensity showed the spatial agglomeration and temporal "inertia" from 2003 to 2017. (2) From the time dimension, the long-term effect of industrial structure first increased and then gradually decreased. (3) From the spatial dimension, industrial structure and investment in anti-pollution projects as percentage of GDP accounted for the main spatial heterogeneity. Furthermore, this paper attempts to provide policy implications to help reduce carbon intensity and achieve carbon neutrality in China. [ABSTRACT FROM AUTHOR]

Under the background of high-quality development led by the new development concept in China, it is imperative to change the development mode, optimize the economic structure, and transform the driving force, and industrial upgrading is the necessary way to promote the optimization of the industrial structure and achieve high-quality economic development. Based on data covering 284 prefecture-level cities in China, this paper first calculates the green total factor productivity (GTFP) of each prefecture-level city and then constructs three spatial econometric models (SLM, SEM, and SDM) based on four spatial weight matrices to empirically analyze the impact of industrial upgrading on GTFP. The results show that the GTFP of all cities in China shows a fluctuating upward trend and significant spatial spillover effect. Both full-sample and regional heterogeneity tests show that industrial upgrading can promote growth in GTFP, but the promoting effect on different regions is different. Regarding the control variables, GTFP has an inverted U-shaped relationship with economic development; additionally, human capital and financial development play a driving role in GTFP, while population density plays a restraining role. Finally, based on the empirical findings, we propose a multipronged policy of differentiated industrial policy and a variety of complementary measures to promote GTFP growth. [ABSTRACT FROM AUTHOR]

Scholars have attempted to compile various multi-region input-output (MRIO) tables for different countries. However, due to city-level data scarcity and methodology constraints, almost no MRIO table covers a large number of cities with more disaggregated sectors in countries with large economies, such as China. Based on two large-scale firm-level datasets, the China Annual Survey of Industrial Firms (CASIF) survey and the China Customs Data (CCD) database, from 2000 to 2013, this paper uses China as a case study and presents a new compilation method to construct an MRIO table covering 284 prefecture-level administrative cities and 334 four-digit sectors, which is by far the most comprehensive MRIO table with the largest number of cities and the most segmented industries in China. Unlike existing MRIO tables constructed based on provincial single-region IO (SRIO) tables, we use information along with various linear constraints implied by sector-level and firm-level statistics. This paper expands on the direct decomposition method by developing auxiliary econometric models necessary for estimations and consistency adjustment. In addition, a comparative analysis shows the reliability of our method, which guarantees better coherence and comparability with the MRIO officially published by the National Bureau of Statistics of China (NBS). Therefore, our proposed methodology provides the possibility of producing more disaggregated MRIO tables in other similar contexts. [ABSTRACT FROM AUTHOR]

Due to the rapid progress of urbanization in China, the percentage of residential energy consumption out of total energy consumption has increased. This paper uses statistical data from 30 Chinese provinces (autonomous regions and municipalities) from 2000 to 2020 to analyze the impact of urbanization on residential energy consumption and construct an econometric model to test the mechanism. The empirical tests show that the consumption of direct energy (energy that exists in nature in its original form and has not been transformed) is positively U-shaped about the urbanization rate. Furthermore, the impact of economic development on direct and indirect energy consumption is significantly positive. In contrast, the effects of population agglomeration on immediate energy consumption are adverse, and the indirect energy consumption is positive. [ABSTRACT FROM AUTHOR]

Correct understanding of the positive role and mechanism of green finance in promoting ecological environment is an important premise and guarantee for promoting green finance to better serve the improvement of ecological environment. Based on the panel data of 31 provinces (municipalities and autonomous regions) in China from 2009 to 2017, this paper constructs a spatial Dubin model based on the distance weight matrix and empirically analyzes the impact of green finance on the ecological environment and its spatial spillover effects. The empirical results show that (1) the development of green finance promotes the improvement of the ecological environment in this region and (2) the influence of green finance on the ecological environment has a significant positive spatial spillover effect, that is, the development of green finance in this region will promote the improvement of the ecological environment in the surrounding areas. [ABSTRACT FROM AUTHOR]

This paper investigates the spatial mechanisms and impacts of land transfer on green total factor productivity (GTFP) in the economically dynamic Yangtze River Delta region of China. Using urban-level panel data from 2007 to 2020 and applying spatial econometric models, the study examines the relationship between land transfer and GTFP. The results of the spatial econometric analysis show that land transfer in the overall Yangtze River Delta region contributes positively to the improvement of GTFP. The mediating mechanism of industrial restructuring and upgrading shows statistically significant effects. Further investigation reveals differences in the spatial interdependence of land transfer on the GTFP among cities in different regions. Land transfer in the core area has significant indirect effects on the GTFP of neighboring cities, while the impact of land transfer in peripheral cities on the GTFP of surrounding cities is less discernible. This suggests that there is still a need for further deepening and development of integration in peripheral cities, as factor integration is still insufficient. The findings of this study provide useful insights for local governments in optimizing land transfer practices and promoting industrial transformation, upgrading, and sustainable green development. [ABSTRACT FROM AUTHOR]

In this paper, the spatial dynamic panel data (SDPD) model with fixed effects is extended to a non-parametric form by relaxing the linear or nonlinear parameter structure of explanatory variables. The non-parametric spatial dynamic panel data (NSDPD) model with fixed effects not only retains the advantages of the SDPD model which can deal with spatial and/or temporal individual characteristics and spatio-temporal dependencies but also solves the limitation that may lead to specification errors. It also enhances the flexibility and practicability of the spatial econometric model. Since the model to be estimated contains unknown functions, we propose this profile maximum likelihood (PML) method to solve the problem of the incidental parameters in the estimation. Under the assumption that the spatial coefficients are known, we first eliminate the influence of the time effect by substitution and then use the local polynomial estimation to preliminarily estimate the unknown function so as to transform the model into the parametric form for solving. We derive the asymptotic properties of PMLEs and find that under certain regularity conditions, both parametric and non-parametric estimators are consistent. The Monte Carlo results show that the estimators have good finite sample performance. We illustrate the empirical relevance of the model by applying it to examine the impact of tourism dynamics on economic development in the Yangtze River Delta region of China. [ABSTRACT FROM AUTHOR]

Haze pollution poses a serious threat to residents' health. In this study, a spatial econometric model of environmental health was established to investigate the direction, intensity, and spatial–temporal heterogeneity of the impact of haze pollution and its spillover effects on public health in 26 cities of the Yangtze River Delta urban agglomerations from 2005 to 2018. The study found that (1) PM2.5 pollution and public health level all show the characteristic of positive spatial correlation and spatial clustering. (2) Haze pollution is the main influencing factor of residents' public health level, with significant negative effects and obvious spillover effects. The urbanization rate, the number of health technicians, and the green area per capita have significant positive impacts on public health. (3) The spatial and temporal heterogeneity of the impact of haze pollution and other factors on public health is obvious. The negative correlation between PM2.5 pollution and public health in eastern cities is higher than that in other cities. Both urbanization rate and green area per capita have a greater positive impact on public health in the northeast of the Yangtze River Delta region. The improvement effect of the number of health technicians on the public health is stronger in the cities of Anhui Province. The research results of this paper provide certain support for the city governments to formulate targeted policies. [ABSTRACT FROM AUTHOR]

The stagnation of growth, huge income gap, and excessive ecological environment degradation are the three issues worldwide. As China entered the stage of high-quality development, it slowed down the economic growth speed and the government paid more attention to social harmony and environment protection. Inclusive green growth efficiency(IGGE) is used to measure the quality of economic development and the degree of coordination among economic, social, and natural systems. Under this background, this paper employs the Data Envelop Analysis (DEA) model to measure IGGE from 2006 to 2019 in 30 provinces of China. Moreover, the temporal and spatial evolution characteristics are revealed and the key drivers of IGGE are explored by the spatial econometric model. The results indicate that the level of provincial IGGI of China has an upward trend in the statistical period and the characteristics of spatial agglomeration have been enhanced. For the drivers of IGGI, the level of opening-up, human capital, and innovation have significant impact on IGGI in China, while other elements are not very important. Finally, some policy suggestions were proposed to promote IGGE in China. [ABSTRACT FROM AUTHOR]

Exploring the impact of transportation development on land price differences between cities is of great significance to help guide the optimal allocation of land resources and promote the coordinated and balanced development of regions. This paper first discusses how regional transportation development influences land price differences between cities at a theoretical level. Then, by taking 26 provincial regions in the Chinese Mainland as research units, the specific effects of provincial transportation development on land price differences between cities are examined empirically by constructing econometric models. The results show that: (a) in recent years, the price of urban land in China has increased significantly, and the land price differences between cities are increasing in most provinces; and (b) provincial transportation development has a narrowing effect on land price differences between cities, and the spatial spillover effect brought by transportation development deserves attention. In the future, the role of transportation development in narrowing regional land price differences should be taken into consideration to promote the balanced development of the land market and the coordinated development of regions. [ABSTRACT FROM AUTHOR]

Based on panel data from 30 provinces in China from 2008 to 2017, this paper constructs a quantile regression econometric model to analyze whether China's environmental regulation has an impact on export trade and to verify whether the Porter hypothesis has been valid in China in recent years. The results show that in the short term, environmental regulations have a restraining effect on export trade, while in the long run, due to the existence of innovation efficiency, environmental regulations will change from having a restraining effect to a promoting effect on export trade. Strict environmental regulations will reduce the production cost of Chinese products, further improve the export competitiveness of Chinese enterprises, and promote export trade. The empirical results verify the conclusion that the Porter hypothesis is confirmed in China. The following three suggestions are proposed for China's exports to promote the win–win of China's green development and export trade: promote the realization of international and domestic double circulation, avoid becoming "pollution shelters" and support technological innovation in environmental protection industries. [ABSTRACT FROM AUTHOR]

Ever since China's "housing reform" in 1998, the level of real estate investment in its cities has continued to rise, leading to the occupation of green space, rapid population concentration, and a severe mismatching of financial resources. At the same time, urban air quality has changed drastically for the worse, with PM2.5 becoming the primary air indicator of concern for many cities in recent years. The existing literature has obtained sufficient results on the influence factors of air pollution, but rarely presents the relationship between real estate investment and air pollution, especially using multiple cities as the sample. This paper thus examines the impact of real estate investment on air quality using a sample of 261 prefecture-level cities in China over the period 1999–2016 through several econometric models. First, the two-way fixed-effect model shows an inverted U-shaped relationship between PM2.5 concentration and real estate investment, but most cities have not yet crossed the turning point, and that real estate investment negatively impacts air quality. Second, the indirect effect of real estate investment on PM2.5 concentration comes from its non-linear impact on urban green coverage, population density, and industrial structure, which has been verified by Hayes and Preacher's (Behav Res 45:627–660, 2010) mediation effect with non-linear forms. Third, heterogeneity analysis indicates that an inverted U-shaped relationship also exists in the subsamples, and that real estate investment in cities with more people, higher GDP, and greater development level is more likely to increase rather than mitigate air pollution. Therefore, cities should promote the green development of real estate and related industries by enhancing environmental awareness, guide the population flow toward the coordinated development between real estate investment and population distribution, and encourage environmentally friendly technological progress via a better rational allocation of financial resources. [ABSTRACT FROM AUTHOR]

This paper theoretically analyzes the direct impact of environmental regulation on carbon emissions and its indirect effects on carbon emissions through foreign direct investment (FDI), energy consumption, industrial structure, and technological innovation. Then, this paper constructs a spatial lag model to empirically test the dual effects of environmental regulation on carbon emissions based on the provincial panel data of 2003–2017 in China. The results show that the average Moran's I value of carbon emissions during 2003–2017 is 0.2506, passing the significance test at 1% level, and carbon emissions have spatial correlation characteristics. The direct impact of environmental regulation on carbon emissions is significant and positive. Environmental regulation could indirectly influence carbon emissions by influencing FDI, energy consumption, and technological innovation, and meanwhile, FDI, energy consumption, and technological innovation help to reduce carbon emissions under the constraint of environmental regulation, specifically. However, the impact of environmental regulation on carbon emissions through industrial structure is not significant. [ABSTRACT FROM AUTHOR]

Purpose – Rural China has been undergoing the “religion fever” since the Reform and Opening-up. By comparing the intergenerational lock-in effects of religious belief with that of non-religious belief, the purpose of this paper is to explain why more and more peasants convert to religion especially Christianity in China. Design/methodology/approach – Data used in this paper comes from a field survey conducted in villages, Funan county. The samples were obtained by the two-stage cluster probability proportional sampling method. Based on the collected survey data, econometric model on the intergenerational lock-in effects of belief was constructed and used for analysis. Findings – Compared with non-religious believers, religious believers can transmit their beliefs more successfully. In addition, the intergenerational lock-in effects of religious beliefs is weakened by oblique socialization in contemporary rural China. Originality/value – This is the first paper focussing on intergenerational transmission of belief in rural China; although many researchers did careful analyses on effects of parents’ belief or religiosity on children’s belief or religiosity in the West, few of them compared the success of intergenerational transmission between different beliefs. This paper fills this gap; as an interdisciplinary study, this paper tries to study religion in economics analysis approaches. This attempt extends research field in Economics and at the same time enriches analysis tools in Religion. [ABSTRACT FROM AUTHOR]

In order to optimize the Chinese medical and health system and improve people's health level, the SFA Malmquist model, the spatial econometric model, and the standard deviation ellipse method were used to measure the efficiency of medical and health services in China's 31 provinces between 2010 and 2020. Study results indicated that the average efficiency value of the 31 provinces generally exceeded 0.8. Specifically, the average efficiency values in the eastern and central regions increased from 0.852 to 0.875 and from 0.858 to 0.88, respectively. In the western and northeastern regions, these values rose from 0.804 to 0.835 and from 0.827 to 0.854, respectively. From the perspective of spatial distribution, there were high-high and low-low clusters in most provinces with significant spatial dependence among them. This analysis reveals that medical and health services efficiency in China demonstrates a spatial pattern extending from northeast to southwest. [ABSTRACT FROM AUTHOR]