Transportation infrastructure upgrading and green development efficiency: Empirical analysis with double machine learning method.

In order to deal with the environmental problems such as pollution emissions and climate change, sustainable development in the field of transportation has gradually become a hot topic to all sectors of society. In addition, promoting the green and low-carbon transformation of China's transportation is also an important issue in the new era. Thus, it is particularly important to correctly identify the green effect of high-speed rail. However, the traditional causal reasoning model faces several challenges such as 'dimensional curse' and multicollinearity. Based on the panel data of 283 prefecture-level cities in China from 2003 to 2019, this study uses the double machine learning model to explore the impact of transportation infrastructure upgrading on the efficiency of urban green development in China. The research shows that the upgrading of transportation infrastructure can effectively improve the efficiency of urban green development by 4%. Service industry agglomeration and green innovation are verified as two mediating channels. Moreover, the synthetic difference in difference model is employed to evaluate the regional impact of high-speed rail, and finds that the regional impact of transportation policies often exceeds the impact of individual cities. We further apply the conclusions of this paper to the research at the micro enterprise level. Goodman-Bacon decomposition and a variety of robustness tests confirm the validity of our conclusions. The study's comprehensive empirical analysis not only validates the positive effects of transportation upgrades on green development, but also offers novel insights into the underlying mechanisms and policy implications of transportation upgrading.

Fostering inclusive green growth in China: Identifying the impact of the regional integration strategy of Yangtze River Economic Belt.

Inclusive green growth has garnered significant attention from governments and international organizations worldwide. Utilizing data from 282 cities in China spanning from 2010 to 2020, this study employs the dual machine learning model and the chain mediated effect model to delve into the effects and internal mechanisms of the regional integration of Yangtze River Economic Belt on inclusive green growth. Our findings indicate that the regional integration of Yangtze River Economic Belt has a substantial influence on inclusive green growth, particularly in cities with a higher degree of marketization, non-industrial cities, and cities lacking natural resource advantages. Mechanistic analysis reveals that the regional integration of Yangtze River Economic Belt exerts its influence on inclusive green growth through three parallel development paths including enhancing urban innovation levels, fostering mass entrepreneurship, and promoting the advancement of digital financial inclusion. Furthermore, the chain mediated effect is supported. Additionally, the spatial spillover effect of target policy is observed. These findings offer empirical evidence regarding the impact of the regional integration of Yangtze River Economic Belt on inclusive green growth, and provide valuable insights for optimizing and enhancing inclusive green growth strategies in China and other emerging economies.

Whether the green credit policy effectively promote green transition of enterprises in China? Empirical analysis and mechanism verification.

Promoting green and low-carbon development has become the consensus of the policymakers and the academic, with green transformation of enterprises being the top priority. This paper adopts the difference-in-difference model to investigate the effect of green credit policy on green transition in China, by utilizing the "Green Credit Guidelines" (2012 Guidelines) policy as a quasi-natural experiment. Using panel data from publicly listed companies in China, an empirical investigation is conducted, we explain the dependent variable from two dimensions: economic performance and environmental performance, leading to the following results. First, the green credit policy affects the economic performance and environmental performance of treated firms positively, and the robust tests confirm the reliability of this primary conclusion. Second, the indirect impact of green credit policy on green transition can be explained through two mediating mechanism channels including internal capacity building and external market attention. In addition, the proposal of "Dual Carbon Targets" makes the impact a slight change. Finally, heterogeneous test also shows that the implementation effect of green credit policy is better in non-state-owned enterprises with high political relevance. These findings are providing valuable insights to promote green transition by designing more effective green credit policies.

Analysis of environmental sustainability and economic development from electricity consumption based on the modified spatial Durbin model.

The study investigates the impacts of financial development, electricity use, and technology innovation on CO2 emissions. International trade also plays an essential role in the economic development of Pakistan. Studying the relationship between ecological parameters, technological innovation, electricity use, and CO2 emissions is necessary to formulate the country's reasonable and practical energy policies. Based on the study's use of data from 292 Pakistani firms from 2006 to 2021, the paper investigates the mechanism of the role between financial development, electricity use, technological innovation, international trade, and CO2 emissions using the spatial Durbin model. The results reveal that the effect of economic growth, electricity use, and technological innovation on CO2 emissions has a spatial spillover effect. The results verify that international trade and the transport sector promote the country's carbon emissions. The typical speculation spike on technology innovation enhanced and financial development should concentrate more on protective ecological parameters. The research provides theoretical guidance for solving the contradictory problem of renewable energy use growth and CO2 emission limitation while promoting green and low-carbon development in the country.

The impacts of casual environmental regulation on carbon intensity in China: Dual mediating pathways of energy low-carbon reconstitution and industrial structure upgrading.

In the new era of global net zero, how to reduce carbon intensity became a hot topic, while few attentions had been paid to the impacts of casual environmental regulation, especially in the emerging economy such as China. In this regard, this study uses the panel data of 30 provinces in China from 2003 to 2019 to study the impacts of causal environmental regulation on the carbon intensity, with the adoption of multiple econometric models. The empirical results show that causal environmental regulation has a significant inhibitory effect on carbon intensity, while at current stage, causal environmental regulation cannot inhibit carbon intensity through the mediating of green innovation and renewable energy production. Fortunately, energy low-carbon reconstitution and industrial structure upgrading are proved to effectively act as the intermediary channels. In addition, the spatial spillover effects and the spatial heterogeneity are supported in the empirical analysis. In a summary, this study starts with the case of China to provide a realistic reference case for the international community, enriches the theory, policy and practice related to environmental regulation, and provides a realistic reference example for emerging economics in a developing country.

Inducement factor of talent agglomeration in the manufacturing industrial sector: A survey on the readiness of Industry 4.0 adoption.

China's economy has progressed from a rapid growth phase to one of high-quality development and innovation. Industry 4.0 manufacturing technology and processes include cyber-physical systems (CPS), Industrial Internet of Things (IIOT), Cognitive Computing and Artificial Intelligence (CCAI) as advancements in computerization and information exchange the relevant variables data, and a survey questionnaire are used to accumulate three-year data from 2017 to 2019. The Structured Equation Modeling (SEM), analytic hierarchy process (AHP), and mediating variable in a SOBEL test are applied. The results show that Industry 4.0 is the primary practical corridor to official and familiar in sequence substitute policy and collaboration for talent agglomeration on research projects. It lowers the fixed price of human capital and significant factors active long-term innovation and profit at the end of the inferential test results. Hypotheses findings show that the associations between dependent and independent variables are essential, and latent variables GFI, CFI, TLI, and IFI have acceptable values. CMINDF and RMR fulfill the fit criteria and results will assist managers and policymakers in spotting talent agglomeration activities implemented to increase manufacturing businesses' readiness to reap the most benefits from Industry 4.0 adoption.

Assessing the air pollution abatement effect of prefabricated buildings in China.

Due to the acceleration of urbanization and industrialization, air pollutants has been increasing, posing a major threat to human health and the ecological environment. During the past period of rapid growth, with the booming development of real estate, the air pollutants brought about by the construction of housing buildings have become more and more serious, especially sulfur dioxide, nitrogen dioxide, and dust, which cast a great threat to human life and seriously jeopardize human health. Compared with the traditional construction of houses, prefabricated buildings construction procedures are reduced, to some extent, can reduce air pollutants. Therefore, this paper takes an empirical perspective to include prefabricated buildings and air pollutants into the same research framework and analyze the inherent logical relationship. We found that prefabricated buildings have a substantial role in mitigating urban air pollution. This conclusion remained solid after various robustness tests including constructing instrumental variables. The effect is observed to be greater in cities above the non-sub-provincial level and those positioned within central regions. The conclusions explore new areas for the green and sustainable development of the construction industry, which in the future will have to fill the requirements of green development in order to survive. Else, perspectives from the construction industry, it provides a realistic solution to economic development and ecological protection, helping to alleviate or resolve the conflict between development and survival.

How does climate policy uncertainty affect green technology innovation at the corporate level? New evidence from China.

The frequent occurrence of extreme weather reminds us to focus more attention on sustainable development. A panel of Chinese A-share listed companies is selected as a research sample to explore how climate policy uncertainty has an effect on companies' green technology innovation. According to the empirical findings, corporate green technology innovation is negatively related to the uncertainty of climate policy. By affecting their R&D investments and risk tolerance, corporations' ability to develop in green technologies has been impacted by the uncertainty of climate policy. We also note that due to the nature of business ownership, the detrimental effect of uncertain climate policy on green technology innovation varies slightly between companies. While environmental regulations reinforce the negative impact of climate policy uncertainty, government subsidies can significantly mitigate this negative impact. These results have important theoretical and practical implications for the development of green economy theory and the realization of energy efficiency in various countries.

Identifying and assessing the multiple effects of informal environmental regulation on carbon emissions in China.

Against the backdrop of the global carbon peak and carbon neutrality goals, the role of informal environmental regulation, epitomized by public engagement, is assuming an increasingly pivotal position within the realm of environmental management. By contrast, amidst the prevailing landscape dominated by formal environmental regulation (command-and-control and market-driven approaches), the environmental effects of informal environmental regulation on carbon emissions have received scant attention. Consequently, we examine the net, nonlinear, and mediation effects of informal environmental regulation on carbon emissions using panel data from 30 provinces in China, from 2003 to 2019. We find that informal environmental regulation has a significant effect on regional carbon emission reduction, especially in the eastern cities, pilot cities, and cities with long-term governor's tenure. Its U-shaped effect is confirmed by changes in environmental decentralization. The key points remain valid after the robustness test and the endogenous processing. The mechanism analysis shows that informal environmental regulation can reduce carbon emissions in the dual channels by improving industrial structure transition and renewable energy substitution. Therefore, this study assesses the management effectiveness of informal environmental regulation and determines the underlying mechanism between it and regional carbon emission reduction to provide a reference and an empirical basis for other countries regarding environmental improvement.

Support for tourism development in Pakistan: A study of road and transportation infrastructure development.

The local population is considered one of the main stakeholders in tourism development. Understanding whether and how road and transport infrastructure is related to local communities' overall attitude toward tourism development is crucial. Scholars have suggested that the overall positive attitude of a local community is associated with its tourism development. This study keeps in view the positive and negative consequences of road and transport development and its relationship with local communities' overall attitude. Drawing on social exchange theory, this study investigates local community support for tourism development using 565 samples from the local community of Gilgit-Baltistan and northern areas of Pakistan. Findings show that community visibility and image enhancement are positively related to the overall attitude of the local community. Infrastructure and urbanization are also positively related to the host community's overall attitude, whereas traffic problems are negatively related to the overall attitude of the local community. However, environmental concerns have an insignificant relationship with the overall attitude of the local community. Overall attitude of local communities is also positively related to support for tourism development. Furthermore, economic benefits positively moderate the relationship between the overall attitude of the local community and its support for tourism development.

The impacts of industrial collaborative agglomeration on industrial sulfur dioxide emissions in China: from the novel perspective of spatiotemporal matrix.

This paper explores the impacts of industrial collaborative agglomeration on industrial sulfur dioxide intensity from a spatiotemporal perspective based on panel data on the 284 prefecture-level cities from 2003 to 2019, with systematic consideration of the underlying mechanism of channels and actions. The empirical results show that industrial co-agglomeration significantly intensifies industrial SO2 intensity, especially with increasing agglomeration. In addition, its positive spatial spillover effects are established in geographical proximity to the city. Furthermore, the channel analysis shows that the industrial structure path, industrial efficiency path, and industrial scale path account for a sharp increase in industrial SO2 intensity. The market forces reverse and moderate this exacerbating process more significantly than the government does, which provides evidence for the importance of pursuing a dynamic equilibrium between them. Finally, there exist heterogeneous effects across cities with different administrative levels, innovation capacities, and macropolicies of special emission limits for air pollutant policy. While arguing for the environmental pollution effects of industrial co-agglomeration, this paper also provides solid support and a new perspective for promoting sustainable economic development and achieving win-win economic and environmental benefits.

The heterogeneous drivers of CO2 emissions in China's two major economic belts: new evidence from spatio-temporal analysis.

CO2 emissions have become increasingly prominent in China, and the primary emitters are economic belts that are spread throughout China. Two major economic belts, i.e., the Yangtze River Economic Belt (YTREB) and the Yellow River Economic Belt (YREB). Combined with stochastic impacts by regression on population, affluence and technology model, the spatial Durbin model under the space-and-time fixed effect and the Geographical and Time-Weighted Regression are employed to explore the spatio-temporal distribution characteristics and heterogeneous drivers of CO2 emissions in the two economic belts. The results are as follows. First, CO2 emissions exhibit obvious spatial correlation features in the YREB, but no such obvious spatial correlation is found in the YRETB. Second, in the YREB, the magnitude of the total influencing factors on CO2 emissions follows an order where affluence (A) is the biggest driver, followed by energy intensity (EI), technology (TEC) and openness (OP), while the biggest driver in the YRETB is industrial structure supererogation (ISS), followed by population (P), energy intensity (EI), and affluence (A). Both direct and spatial spillover effects of the drivers are observed in the two economic belts. Third, the CO2 emissions show a notable temporal lag effect in the YREB, but not in the YRETB. Fourth, the effects of the CO2 emission drivers illustrate significant spatio-temporal heterogeneity in the two economic belts.

How does national development zone policy affect carbon emissions in China? New evidence from a quasi-natural experiment.

The expansion of China's development zones has made great contributions to economic development, as well as provided practical guidance for other developing countries to implement development zone policies. However, in the context of global advocacy of low carbon, literature about how the development zone policy affect carbon emissions is poor, especially in China at the urban level. Therefore, this study takes China's development zone policy as a quasi-natural experiment, using the panel data of 285 cities in China from 2003 to 2020, and adopting the DID model to analyze its impact on carbon emissions. After a series of robustness tests including placebo test, dynamic test (all independent variables are lagged by one period), endogeneity test, and parallel trend test, the results are basically robust. The findings show that the development zone policy indeed significantly reduces carbon emissions. In addition, we find that cities with higher resource endowments, cities in the eastern and central regions, and other larger cities across the country have better carbon emissions reduction effects. To a certain extent, the research in this paper fills the gap of theoretical research on carbon emissions in terms of the development zone policy, and provides some practical basis for future research in the field of carbon emissions.

Identifying impacts of industrial co-agglomeration on carbon emissions: Evidence from China.

Based on panel data of 285 cities in China at the prefecture level and above from 2005 to 2020, this paper aims to study the nexus between industrial co-agglomeration and carbon emissions from dual perspectives including space and time. It adopts multiple approaches including a dynamic general method of moment, panel quantile regression model, panel threshold model, and dynamic spatial Durbin model. The non-spatial empirical results support the establishment of the threshold effect and the imbalance effect. The spatial empirical results indicate that industrial co-agglomeration poses a dramatic stimulating effect on urban carbon emissions, and its spatial spillover effect and spatial heterogeneity are conditionally established. Furthermore, heterogeneous effects are supported, such as the positive spillover effects of industrial co-agglomeration are more significant in western cities, resource-oriented cities, and non-low-carbon pilot cities. The heterogeneous influence of cost factors on industrial agglomeration and carbon emissions has also been partially confirmed. In terms of the channels and mechanism of action, the negative externalities of industrial co-agglomeration occupy a dominant position in the current status of economic development. The dynamic equilibrium between government intervention and marketization is a solid foundation for the optimization of carbon emission reduction paths.

Campaign-style governance of air pollution in China? A comprehensive analysis of the central environmental protection inspection.

Central environmental protection inspection (CEPI) is a major institutional innovation in China's environmental governance, but its effectiveness in improving air quality is still unclear. However, the effectiveness of CEPI is of great significance and can be regarded as an important reference for deepening the reform of environmental governance system in China. This article takes the CEPI as a quasi-natural experiment and uses the regression discontinuity design (RDD) and the difference-in-differences (DID) methods to examine the effectiveness of this policy. The study found that the first round of CEPI reduced the air pollution of cities in the inspected provinces in a short time. Moreover, this positive policy effect persisted in the aftermath of the inspection, but this long-term effect is mainly reflected in PM10 and SO2. Heterogeneity analysis showed that CEPI was only effective in reducing air pollutants of industry-oriented cities, cities in Central and Eastern China, and cities with large or small population size. The moderating effect analysis indicated that a healthy relationship (close and clean) between the local governments and businesses was conducive to reducing air pollution. The research confirmed the presence of "selective" reduction of air pollutants in the long run caused by CEPI, thereby providing new inspiration for the improvement of campaign-style environmental governance and the follow-up CEPI work.

The Impact of Financial Literacy on Household Health Investment: Empirical Evidence from China.

Based on the 2019 China Household Finance Survey (CHFS) data, this paper used factor analysis to measure the level of financial literacy of surveyed householders and used the Probit model and the negative binomial model to test the impact of financial literacy (FL) on household health investment (HHI). The results show that: (1) FL is an essential influencing factor in increasing participation in HHI, and householders with a higher level of FL are also more willing to pay for diversified investments. (2) We split the FL level from the two dimensions of knowledge and ability. We found that the primary FL (including financial knowledge, computing ability, and correct recognition of investment product risk) plays a more critical role in the investment decision process. (3) When information sources, health knowledge, and family income are used as mediating variables, FL can influence the decisions of HHI in three ways: expanding information sources, enriching health knowledge, and alleviating income constraints. (4) By analyzing the heterogeneity of household heads in different regions and with different personal characteristics, we found that the medical level of the household location and the life and work experience of the householders played a moderating role.

The effectiveness of smart city policy on pollution reduction in China: new evidence from a quasi-natural experiment.

Based on panel data of 285 prefecture-level and above cities in China from 2003 to 2020, this study has explored the impacts of smart city policy (SCP) on environmental pollution by utilizing the difference-in-differences (DID) model and its derived models. The results indicate that SCP can significantly reduce environmental pollution, and this conclusion still holds after passing numerous robustness tests, such as the propensity-score-matching difference-in-differences (PSM-DID) test, the placebo test, all independent variables lagging one period test, the policy interference test, and the instrument variable (IV) test. Moreover, the heterogeneity analysis shows that the effect of reducing environmental pollution of SCP is heterogeneous. Furthermore, the results of the spatial difference-in-differences (SDID) model show that SCP has a "beggar-thy-neighbor" effect among the pilot cities, and there is no spillover effect of SCP on pollution reduction in neighboring non-pilot cities. Finally, the analysis of moderating effect reflects that the government intervention plays a negative inhibition role in the process of SCP affecting environmental pollution, while the market competition plays a positive catalytic role in the process of SCP reducing environmental pollution.

Suspension culture strategies to enrich colon cancer stem cells.

How to efficiently obtain high-purity cancer stem cells (CSCs) has been the basis of CSC research, but the optimal conditions for serum-free suspension culture of CSCs are still unclear. The present study aimed to define the optimal culture medium composition and culture time for the enrichment of colon CSCs via suspension culture. Suspension cell cultures of colon cancer DLD-1 cells were prepared using serum-free medium (SFM) containing variable concentrations of epidermal growth factor (EGF) and basic fibroblast growth factor (bFGF) to produce spheroids. Culture times were set at 10, 20 and 30 days. A total of nine different concentrations of EGF and bFGF were added to SFM to generate nine experimental groups. The proportions of CD44+, CD133+, and CD44+CD133+ double-positive spheroid cells were detected via flow cytometry. mRNA expression of stemness-, epithelial-mesenchymal transition- and Wnt/ß-catenin pathway-associated genes was determined via reverse transcription-quantitative PCR. Self-renewal ability was evaluated by a sphere-forming assay. Tumorigenesis was studied in vitro using a colony formation assay and in vivo via subcutaneous cell injection in nude mice. It was found that the highest expression proportions of CD133+ and CD44+ spheroid cells were observed in group (G)9 (20 ng/ml EGF + 20 ng/ml bFGF) at 30 days (F=123.554 and 99.528, respectively, P<0.001), CD133+CD44+ cells were also observed in G9 at 30 days (and at 10 days in G3 and 20 days in G6; F=57.897, P<0.001). G9 at 30 days also displayed the highest expression of Krüppel-like factor 4, leucine-rich repeat-containing G protein-coupled receptor 5, CD44, CD133, Vimentin and Wnt-3a (F=22.682, 25.401, 3.272, 7.852, 13.331 and 17.445, respectively, P<0.001) and the lowest expression of E-cadherin (F=10.851, P<0.001). G9 at 30 days produced the highest yield of cell spheroids, as determined by a sphere forming assay (F=19.147, P<0.001); colony formation assays also exhibited the greatest number of colonies derived from G9 spheroids at 30 days (F=60.767, P<0.01), which also generated the largest mean tumor volume in the subcutaneous tumorigenesis xenograft model (F=12.539, P<0.01). In conclusion, 20 ng/ml EGF + 20 ng/ml bFGF effectively enriched colon CSCs when added to suspension culture for 30 days, and conferred the highest efficiency compared with other combinations.

How does the air pollution prevention and control action plan affect sulfur dioxide intensity in China?

As a part of China's efforts to mitigate and control air pollution in key areas, the Air Pollution Prevention and Control Action Plan was implemented in 2013, and several regulatory measures were introduced. Based on the data from 271 prefecture-level cities between 2008 and 2018, the difference-in-differences model is used to explore the effect of it on sulfur dioxide intensity in our study, and several significant results are as follows: (1) The baseline results suggest a 23% reduction in sulfur dioxide intensity in pilot cities compared to non-pilot cities. (2) The total factor productivity fails to play a partial mediating role in reducing the sulfur dioxide intensity under the implementation of the policy. (3) The results of the triple differences model suggest that the policy still exerts significant adverse effects on sulfur dioxide intensity in the pilot areas of the carbon emission trading scheme.

A propensity score matching investigation of short-term results of single-incision laparoscopic low anterior rectal resection via ileostomy site.

Aims: The study was performed to verify the results of single-incision laparoscopic surgery (SILS) through the ileostomy site for low rectal cancer compared with conventional laparoscopic surgery (CLS). Materials and Methods: From January 2019 to November 2021, 133 patients with low rectal cancer underwent single-incision (n = 27) or conventional (n = 106) methods of low anterior rectal resection surgery with ileostomy. All patients were balanced by propensity score matching for basic information in a ratio of 1:2, resulting in 27 and 54 in SILS and CLS groups, respectively. Results: Relative to the CLS group, the SILS group exhibited fewer leucocyte changes, shorter time to first exhaust and first bowel sounds, shorter length of hospital stay and lower Visual Analogue Score on post-operative days (POD2) and POD3. Intraoperative or post-operative complications or readmissions were comparable between the two groups. The oncologic results remained consistent between the two groups other than the number of lymph nodes dissected in group no. 253. Conclusions: Single-incision laparoscopic low rectal resection surgery through the ileostomy site has advantages in terms of reduced post-operative pain, shorter post-operative exhaust time and length of hospital stay while also achieving oncologic outcomes similar to those of conventional laparoscopy. It can be an alternative procedure for patients with low rectal cancer who require ileostomy.