How does green manufacturing enhance corporate ESG performance? - Empirical evidence from machine learning and text analysis.

Green manufacturing, widely recognized as a crucial avenue for companies to achieve sustainable competitive advantages, exerts significant spillover effects on both environmental protection and social responsibility. Accordingly, this can significantly enhance corporate Environmental, Social, and Governance (ESG) practices and enhance overall ESG performance. This study focuses on Chinese A-share listed firms between 2009 and 2022, characterizing their ESG performance.

The impact of nitrogen Fertilizer application on air Pollution: Evidence from China.

We examine the effects of nitrogen fertilizer application on air pollution in China. Distinct from the existing literature that tends to utilize field sampling method, we construct a comprehensive panel dataset and discover that 1 g nitrogen increase in fertilizer correlates with a rise of 0.55 μg/m³ in PM concentrations.

The longitudinal relationship between tourism, electricity consumption, and CO emissions.

The objective of the study is to determine the electricity use, and tourism industry environmental impacts, and increase in CO emissions in Pakistan. What are the linkages of foreign direct investment, intercountryal trade, gross domestict product, and CO emissions. The study has applied the Autoregressive distributed lag (ARDL) method to analysis the data set from 1985 to 2023.

PCAlign: a general data augmentation framework for point clouds.

With the advancement of 3D scanning technologies and deep learning theories, point cloud-based deep learning networks have gained considerable attention in the fields of 3D vision and computer graphics. Leveraging the rich geometric information present in 3D point clouds, these networks facilitate more accurate feature learning tasks. However, existing networks often suffer from generalization defects caused by variations in pose and inconsistent representations of training data.

Uncovering the impact and mechanisms of air pollution on eye and ear health in China.

Increasing air pollution could undermine human health, but the causal link between air pollution and eye and ear health has not been well-studied. Based on four-week-level records of eye and ear health over 1991-2015 provided by the China Health and Nutrition Survey, we estimate the causal effect of air pollution on eye and ear health. Using two-stage least squares estimation, we find that eye or ear disease possibility rises 1.

The effect of air pollution on defensive expenditures: Evidence from individual commercial health insurance in China.

To mitigate the substantial losses incurred by air pollution, individuals undertake defensive behaviors in the form of health insurance expenses. Leveraging data from the 2011-2017 China Household Finance Survey (CHFS) encompassing 3033 residents, we estimate the causal impact of air pollution on defensive expenditures. Our findings are as follows: (1) Air pollution exhibits a significantly favorable effect on individual commercial health insurance expenses, with a 1% increase in PM concentration correlating to an 11.

Uncertainty quantification in high-dimensional linear models incorporating graphical structures with applications to gene set analysis.

Motivation: The functions of genes in networks are typically correlated due to their functional connectivity. Variable selection methods have been developed to select important genes associated with a trait while incorporating network graphical information. However, no method has been proposed to quantify the uncertainty of individual genes under such settings.

Effect of water Resource utilization in Poyang lake area on carbon emissions based on decoupling theory.

The utilization of regional water resources has the potential to impact carbon emissions. Maintaining a decoupled relationship between water resources and carbon emissions facilitates harmonious regional development. Understanding the mechanism of their coordination is conducive to achieving the "Double Carbon" goal and control of regional carbon emissions and water resource consumption.

Spatial-structural analysis of macroeconomic factors' impact on carbon emissions in East Africa: a spatial econometric panel study.

Despite the abundance of research on reducing carbon emissions, there is a significant gap in understanding the influence of macroeconomic factors on carbon dioxide (CO) emissions from a spatial-structural perspective. This study aims to contribute to the literature by investigating the impact of macroeconomic factors on carbon dioxide emissions in six East African countries between 1989 and 2020. Using spatial econometric panel models, the study analyzed spatial dependence among the variables.

Effects of human inequality and urbanization on ecological well-being performance: A System-GMM analysis.

Enhancing the efficiency with which ecological consumption is transformed into human well-being is a necessary condition for achieving sustainable development. However, the current literature lacks systematic methods and applications for scientifically assessing Ecological Well-being Performance (EWP). How to value and index EWP is crucial to improve EWP.

Testing serial correlation in a general -factor model with possible infinite variance.

It is well-known that the presence of serial correlation may result in an inefficient or even biased estimation in time series analysis. In this paper, we consider testing serial correlation in a general -factor model when the model errors follow the GARCH process, which is frequently used in modeling financial data. Two empirical likelihood-based testing statistics are suggested as a way to deal with problems that might come up with infinite variance.

Research on the influencing factors of promoting flipped classroom teaching based on the integrated UTAUT model and learning engagement theory.

With the rapid advancement of educational technology, the flipped classroom approach has garnered considerable attention owing to its potential for enhancing students' learning capabilities. This research delves into the flipped classroom teaching methodology, employing the Unified Theory of Acceptance and Use of Technology (UTAUT), learning engagement theory, and the 4C skills (comprising communication, collaboration, creativity, and critical thinking) to investigate its effects on learning capabilities. The research surveyed 413 students from three universities in Jiangxi Province, employing stratified random sampling.

Does digital inclusive finance promote carbon emission reduction of enterprises.

Can the information technology revolution lead to carbon emission reduction for firms? This study extends the limited evidence in the literature and investigate the role and mechanism of digital inclusive finance on enterprises' carbon emissions using panel data of 247 prefectural-level cities and 6019 industrial enterprises in China. Our findings indicate that digital inclusive finance can promote enterprise carbon emission reduction, and this effect remains significant after the instrumental variable estimation test. The effect has regional heterogeneity and the development of digital inclusive finance in the area east of Hu Huanyong line has a significant impact on reducing enterprise carbon emission.

Does air pollution fuel irrational behaviors in stock investments?

This paper investigates the influence of air pollution on irrational behaviors in stock trading through behavioral experiments in laboratory, simulating air pollution by burning straw and mosquito coils. The results of this study show that air pollution significantly improves disposition effect and repurchase effect in an asymmetric way, which are thought as irrational behaviors in stock investments, making subjects prefer selling winning stocks (part of disposition effect) and repurchasing stocks that have fallen in price since the sale (part of repurchase effect). Furthermore, regret, a negative emotion, is the psychological mechanism by which air pollution influences the irrational behaviors.

Improve energy use efficiency through free trade policy: evidence from the establishment of free trade zones in China.

In the context of increasing global resource and environmental problems, it is of great practical significance to accurately test the impact of various factors on energy use efficiency for maintaining national energy security and formulating relevant policies. This paper measures firms' total factor energy efficiency (TFEE) using the two-stage stochastic frontier method within the data envelopment analysis (DEA) framework, leveraging data from listed firms in China spanning 2010 to 2022. Employing the establishment of free trade zones (FTZs) as a quasi-natural experiment, we apply the staggered differences-in-differences (DID) and stacked DID methods and analyze the impact of FTZs on firms' TFEE.

Investigating the crowding effect of FDI on domestic investments: Evidence from Bangladesh.

This study empirically investigates the crowding effect of Foreign Direct Investment (FDI) on domestic investments in Bangladesh, utilizing annual time series data from 1972 to 2022. Initially, unit root tests are conducted with and without considering structural breaks in the dataset. This study employs the Johansen test of cointegration to investigate the enduring association between the variables and utilizes the Vector Error Correction Model (VECM) to accommodate this relationship over the long term.

Unveiling the influence of global innovation networks on corporate innovation: evidence from the international semiconductor industry.

In this study, we investigate the influence of global innovation networks (GINs) on the innovation output of semiconductor firms. Utilizing negative binomial regression and network analysis, we assess how network positions, specifically degree, betweenness, and closeness centrality, affect firms' innovation performance, revealing significant positive impacts. Moreover, our results identify a positive U-shaped relationship between structural holes in GINs and innovation performance, suggesting that while moderate network engagement aids innovation, too much can be detrimental.

Will advancement in technologies bring fear and damage human employment? Evidence from China's manufacturing industry.

Advancement in technologies such as robotic industries and artificial intelligence bring fear among human being that jobs will be substituted by robots. Base on the panel data of 28 China's manufacturing industries, this research analyzed the impact of technical progress bias on employment. First, we calculate the technical progress bias index of 28 industries base on the stochastic frontier model with transcendental logarithm function found 16 industries were toward the skilled labor while the remaining 12 industries were toward the unskilled labor.

Digital inclusive finance, green technological innovation, and carbon emissions from a spatial perspective.

Based on the panel data of 276 prefecture-level cities in China from 2011 to 2020, this study explores the impact of digital inclusive finance (DIF) on carbon emissions and the intrinsic mechanism of green technological innovation from a spatial perspective by constructing a spatial econometric model, a mediating effect model, and a threshold model. The results show that DIF significantly inhibits carbon emissions, exhibiting a spatial spillover effect. The transmission mechanism from a spatial perspective shows that green technological innovation plays a partial mediating role between DIF and carbon emissions, with the mediating effect accounting for approximately 59.

Changes in the labor share of enterprises under the green and low-carbon transition: Empirical evidence from China's carbon emission trading pilot.

Green and low carbon reflect the high-quality development, while income distribution is an indicator of the balance of development. Is there a lack of fairness in the process of green and low carbon transition of enterprises? Using data from A-share listed companies from 2009 to 2016, this paper constructs a DID identification framework for controlling the endogeneity problem using the 2013 carbon trading policy pilot as a quasi-natural experiment to empirically test the impact of corporate low-carbon transformation on corporate labor income share in the context of carbon trading policy. The findings indicate that carbon trading policy decreases the labor income share of firms.