Efficiency evaluation of China's transportation system considering carbon emissions: Evidence from big data analytics methods

China's transportation sector is a vital link between production and consumption, but it also has issues with low efficiency, high carbon emissions, and technological bottlenecks. To improve efficiency and provide actionable recommendations and strategies, this study first constructs a comprehensive evaluation index system to gauge the transportation sector's inputs using panel data from different Chinese provinces from 2007 to 2021. Within the assessment system, the principal component analysis (PCA) method is used to reduce the dimension of the indexes, thereby yielding a set of adjusted inputs. Subsequently, the transportation system efficiency (TSE) is evaluated using the super-efficiency SBM-DEA model, which includes unexpected outputs such as carbon emissions, and three-stage DEA modifies the efficiency. Then, we calculate the Malmquist-Luenberger index (TML) and its components: technological change (TTC) and technological efficiency change (TEC). Lastly, the influential factors impacting TSE are analyzed via a truncated regression Tobit model. The following are the conclusions: (1) The transportation industry in China exhibits inefficiency, and the average TSE in Stage I and III is 0.91 and 0.93, respectively. TSE is underestimated due to the influence of external environmental factors and inefficiencies in management in Stage I. (2) TSE in the eastern area also produces significant carbon emissions that surpass the national average. At the same time, other regions face efficiency limitations due to geographical constraints and management obstacles. (3) Insufficient technical capacity is a major cause of inefficiency in the transport sector and is prevalent in the northeast, west, and central regions. (4) Population growth and income per capita advancements foster transportation industry development, while increased GDP, fiscal revenues, and traffic accidents contribute to declining efficiency. The study above findings serve as a foundation for regional and national management initiatives and policies to enhance transportation effectiveness.

Optimization of coupling crop and livestock production system's eco-efficiency in northern China based on a life cycle assessment and data envelopment analysis method

Under the twin pressures of global food security and dual‑carbon strategies, improving farm eco-efficiency is critical for achieving China's goal of a 50 Pg increase in grain production, meeting the ambitious climate mitigation targets set by the Paris Agreement, and meeting seven of the seventeen Sustainable Development Goals (SDGs) set by the United Nations. However, there is limited research on eco-efficiency measures supported by localised fine-scale data and coupling mechanisms for the structure, production process, efficiency improvement, and carbon reduction synergies of integrated farming systems in China. This study used the Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) methods to assess eco-efficiency at the farm level in northern China, included in the National Coupling Crop and Livestock Production Pilot Programs, to improve the eco-efficiency of farms to achieve increased production and emission reductions. The results showed that the overall eco-efficiency of farms was in the lower-middle range, with only 20.18 % of the farms having a technical efficiency exceeding 1. Problems included a backward level of pure technical efficiency and a return to scale. Non-integrated farms have the lowest profitability (41.33 %) and the highest carbon emission intensity of 3.03 kg CO2eq/USD. The global warming potential impact of non-integrated farms optimization could be reduced by 25 Pg CO2eq. Implementing the integrated farming mode has a significant advantage in reducing carbon emissions and improving productivity. Overall, farm fodder optimization can be increased by up to 42.41 %. Simultaneously, farms with sufficient farmland are more likely to realise a highly integrated business mode for crop cultivation and livestock breeding. Therefore, constructing a new type of green integrated farming system will help farms achieve increased production and emission reductions, promote the development of sustainable agriculture, and provide a Chinese model for the realisation of global SDGs.

Study on the measurement of coupling and coordinated development level between China's internet and elderly care services and its influencing factors

BACKGROUND

With the intensification of China's aging population, the demand for elderly care services has become increasingly prominent. At the same time, rapid development of internet technology provides more convenience and possibilities for the elderly. However, the coordinated development between the internet and elderly care services still faces challenges. This study aims to measure the level of coupling and coordinated development between the internet and elderly care services in China, and analyze the influencing factors, in order to provide reference for promoting elderly care services.

METHODS

In this paper, the entropy method and coupling coordination degree model were used to measure the coupling coordination development index of the internet and elderly care services in China from 2012 to 2021. In addition, considering that the coordinated development between the two is affected by many factors, the Tobit model was used to analyze the main factors affecting the integration of the internet and elderly care services.

RESULTS

(1) The coupling and coordination of the Internet and senior care services is in its infancy, but the coupling and coordination of the two is on the rise, and there is still a lot of room for development in the future. (2) In terms of time scale, the coupling coordination development level between the internet and elderly care services in China has gone through three stages of "disorder recession-transition coordination-coordinated development". (3) In terms of influencing factors, government management ability has a more positive impact on the development of the integration of the Internet and senior care services, financial support, scientific and technological investment and the level of innovation play a mild pulling role, while the level of informatization to a certain extent restricts the level of integration of the Internet and senior care services.

CONCLUSION

In order to promote the coordinated development of China's Internet and senior care services, it is necessary to comprehensively understand the current situation and development space of China's Internet and senior care services coupling coordination degree, accurately grasp the dynamic trend of China's Internet and senior care services coupling and coordinated development, promote the stage of leapfrogging, and fully consider the influencing factors, so as to realize the optimal allocation of policies and resources. These measures will help to promote a more coordinated and sustainable development of the internet and elderly care services in China.

Mixture of regressions with multivariate responses for discovering subtypes in Alzheimer's biomarkers with detection limits

There is no gold standard for the diagnosis of Alzheimer's disease (AD), except from autopsies, which motivates the use of unsupervised learning. A mixture of regressions is an unsupervised method that can simultaneously identify clusters from multiple biomarkers while learning within-cluster demographic effects. Cerebrospinal fluid (CSF) biomarkers for AD have detection limits, which create additional challenges. We apply a mixture of regressions with a multivariate truncated Gaussian distribution (also called a censored multivariate Gaussian mixture of regressions or a mixture of multivariate tobit regressions) to over 3,000 participants from the Emory Goizueta Alzheimer's Disease Research Center and Emory Healthy Brain Study to examine amyloid-beta peptide 1-42 (Abeta42), total tau protein and phosphorylated tau protein in CSF with known detection limits. We address three gaps in the literature on mixture of regressions with a truncated multivariate Gaussian distribution: software availability; inference; and clustering accuracy. We discovered three clusters that tend to align with an AD group, a normal control profile and non-AD pathology. The CSF profiles differed by race, gender and the genetic marker ApoE4, highlighting the importance of considering demographic factors in unsupervised learning with detection limits. Notably, African American participants in the AD-like group had significantly lower tau burden.

Research on agri-environmental technology efficiency--take Jilin Province in China as an example

From the perspective of the world agricultural development law, agricultural economic development and ecological environmental protection usually fall into a dichotomy paradox, according to the history of agricultural development in developed countries, they also experienced the rapid development of agriculture led to the destruction of the agro-ecological environment, which has become a key element hindering the sustainability of agriculture. Subsequently, developed countries rely on modern technology to achieve the transition from traditional agriculture to modern agriculture, crossing the paradoxical trap of economic development and ecological construction. At the present stage, China also shows the sharp contradiction between agricultural development and ecological construction, the traditional agricultural production methods of agricultural output has basically reached the limit, however, the established production methods of the ecological environment caused by the negative effects of the more and more serious, so that the agricultural environmental technology efficiency is not optimistic, so there is an urgent need to have a clear understanding of the main grain-producing areas of China's agricultural environmental technology efficiency and the factors affecting it. As an important grain producing area in China, Jilin Province's agricultural development level is in the forefront of the country, and it is also facing the contradiction between agricultural development and ecological environmental protection at the present stage. In order to realize the green transformation of agriculture and improve the technical efficiency of agricultural environment, it is necessary to rely on the optimisation of multi-dimensional factors such as technology and system. The study of agricultural environmental technical efficiency in Jilin Province has important theoretical significance and practical value for guiding other agricultural areas to realize the green transformation of production mode.

Joint modeling approaches for censored predictors due to detection limits with applications to metabolites data

Measures of substance concentration in urine, serum or other biological matrices often have an assay limit of detection. When concentration levels fall below the limit, exact measures cannot be obtained, and thus are left censored. The problem becomes more challenging when the censored data come from heterogeneous populations consisting of exposed and non-exposed subjects. If the censored data come from non-exposed subjects, their measures are always zero and hence censored, forming a latent class governed by a distinct censoring mechanism compared with the exposed subjects. The exposed group's censored measurements are always greater than zero, but less than the detection limit. It is very often that the exposed and non-exposed subjects may have different disease traits or different relationships with outcomes of interest, so we need to disentangle the two different populations for valid inference. In this article, we aim to fill the methodological gaps in the literature by developing a novel joint modeling approach to not only address the censoring issue in predictors, but also untangle different relationships of exposed and non-exposed subjects with the outcome. Simulation studies are performed to assess the numerical performance of our proposed approach when the sample size is small to moderate. The joint modeling approach is also applied to examine associations between plasma metabolites and blood pressure in Bogalusa Heart Study, and identify new metabolites that are highly associated with blood pressure.

Measurement and influencing factors of carbon emission efficiency based on the dual perspectives of water pollution and carbon neutrality

The achievement of the 'Carbon Dioxide Removal' vision has become a crucial strategic objective for national development. However, the carbon emissions produced during wastewater treatment processes hinder the attainment of the 'Carbon Dioxide Removal' targets. Addressing water pollution is not only essential for achieving the goal of 'carbon dioxide removal' but also for enhancing the carbon emission efficiency (CEE). In order to evaluate the CEE of five provinces in the Northwest of a certain developing country in East Asia from 2011 to 2020, this paper proposes a new method that calls the super-efficiency SBM model with unexpected output. Then, the study also analyzes the temporal and spatial evolution characteristics by generating kernel density curves. Furthermore, the Tobit panel regression model is used to examine the factors that influence CEE and analyze the internal mechanisms and reasons behind these factors. Finally, a tailored treatment policy is suggested based on the local water pollution situation. The results show that: (1) The CEE of the entire study area exhibited a consistent upward trend over time. By the conclusion of the study period, the efficiency value had not yet reached 1. (2) Based on the year 2015 as a turning point, the overall gap in CEE of researched areas shows a tendency of first narrowing and then gradually widening. (3) The level of economic development, industrial structure, and green innovative technology are positively correlated with CEE. Conversely, there is an inverse relationship between CEE and the level of urbanization and energy consumption. Through the research conclusion and the reality of water pollution, the policy suggestions to improve the efficiency of urban carbon emission.

Agricultural tridimension pollution emission efficiency in China: An evaluation system and influencing factors

We innovated traditional one-sided agricultural carbon emission efficiency research, comprehensively explored the agricultural tridimension pollution emission efficiency (ATPEE), constructed an ATPEE evaluation system considering technological heterogeneity characteristics based on the meta-frontier nonradial directional distance function (NDDF) model in a total-factor framework, evaluated the ATPEE in 30 mainland China provinces from 1997 to 2021 for the first time, and empirically studied the factors influencing the ATPEE in China with the Tobit model. The results showed the following: (1) ATPEE improvement potentials of 75.16 % and 50.88 % occur under the meta and group frontiers, respectively. (2) The eastern region represents the potential optimal agricultural tridimension pollution emission technology, while the central and western regions exhibit a large gap with the national potential optimal technology level. (3) The ATPEE loss in the eastern and western regions mainly results from management inefficiency, while that in the central region largely results from technology gap inefficiency. (4) The effects of the industrialization rate, urban-rural income gap, agricultural production structure, financial support for agriculture, natural conditions and effective irrigation rate on the ATPEE in the different regions vary.

Effects of School Physical Education on the Exercise Habits of Children and Adolescents: An Empirical Analysis Using China Health and Nutrition Survey Data

BACKGROUND

Since 2002, the Chinese Ministry of Education has conducted reform in the physical education (PE) curriculums of schools in China, with a focus on shifting from sports skills to regular participation in physical activity (PA) and promoting health. The aim of the study, therefore, is to examine the effects of school PE on the exercise habits of children and adolescents in China over time.

METHODS

Data based on 5941 observations of 3708 individuals aged 6 to 17 were collected from the China Health and Nutrition Survey (CHNS) for the period 2004 to 2015. The data were analyzed using the fixed-effect Logit model and the random-effect Tobit model.

RESULTS

The likelihood of exercising outside of school is 20.2% higher for students who have school PE than those who do not. Our study found that increasing the duration of PE at school by 100%, increases the duration of out-of-school PA by 22.3%. The variety of the types of sports schools offer encourages students to participate in out-of-school physical activity. The likelihood of students exercising outside of school increases by 5.6% when 1 more exercise type is provided in school PE. In addition, soccer, basketball, badminton, and volleyball education increases students' participation in after-school exercises. Soccer and basketball education, in particular, improves the duration of after-school PA.

CONCLUSIONS

To form exercise habits in children and adolescents, we encourage the promotion of a variety of physical activities in schools, especially team sports such as soccer and basketball.

Spatiotemporal evolution and influencing factors of water resource green efficiency in the cities of the Yangtze River Economic Belt

Effectively utilizing water resources, which is a fundamental natural resource and a vital economic resource, directly impacts how a country's economy develops. In this study, the Super-SBM model is used to calculate the city water resource green efficiency (CWRGE) of the Yangtze River Economic Belt (YREB), 108 cities that are prefecture level or higher, from 2006 to 2021. And its temporal and spatial evolution as well as its affecting variables are examined. The results indicate that, as a whole, the YREB's CWRGE has not yet achieved an effective level. The CWRGE in the YREB generally exhibits a trend of "first decreasing and then increasing, then decreasing and then increasing" and shows a "W"-shaped evolution law, and the overall trend is upward. There are just seven cities with effective data envelopment analysis (DEA), namely Changzhou, Hangzhou, Shanghai, Xuzhou, Changde, Changsha, and Yuxi. During the reporting period, the CWRGE of cities of various scales showed significant gaps: mega cities > big cities > small and medium-sized cities. From a regional perspective, the highest rate of CWRGE was found downstream of the YREB cities, then upstream, and the middle was the lowest. Spatial correlation findings demonstrated that both the agglomeration range and the outlier range were distributed, and there were mainly two positive aggregations of space forms ("high-high (H-H) type" and "low-low (L-L) type"), and the spatial distribution changed. The results of the spatiotemporal evolution demonstrate that there are more and more cities with high efficiency, as well as cities with low efficiency. From the results of the Tobit regression model, the CWRGE in the YREB are significantly improved by the economical development level, industrial scale, and water usage structure. While foreign direct investment and environmental regulation have considerable detrimental impacts, the impact of scientific and technological investment is not significant.

Analysis of the impact and moderating effect of high-density development on urban flooding

Although previous studies have posited that the high-density development of urban buildings and infrastructure contributes to urban flooding, empirical analyses and in-depth investigations into the interaction factors have remained limited. This study aims to analyze the influence and moderating effect of high-density development on urban flooding. Thus far, various land-use and interaction factors related to urban development density have been explored. Subsequently, the urban watershed was selected, utilizing panel data 2002 to 2017, and employing the Tobit model for analysis. The analysis revealed that high-density development had an adverse effect on urban flooding and that the runoff characteristics of high-density development were not limited to those of impervious surfaces. The horizontal and vertical aspects of dense buildings and structures acted as sub-watersheds that increased the time to reach peak flow. Moreover, high-density development had a moderating effect in low-lying areas. The results of this study underscore the necessity of urban disaster prevention planning to consider the direct and indirect effects, as well as the runoff characteristics, of high-density development on urban flooding.

A threshold longitudinal Tobit quantile regression model for identification of treatment-sensitive subgroups based on interval-bounded longitudinal measurements and a continuous covariate

Identification of a subgroup of patients who may be sensitive to a specific treatment is an important problem in precision medicine. This article considers the case where the treatment effect is assessed by longitudinal measurements, such as quality of life scores assessed over the duration of a clinical trial, and the subset is determined by a continuous baseline covariate, such as age and expression level of a biomarker. Recently, a linear mixed threshold regression model has been proposed but it assumes the longitudinal measurements are normally distributed. In many applications, longitudinal measurements, such as quality of life data obtained from answers to questions on a Likert scale, may be restricted in a fixed interval because of the floor and ceiling effects and, therefore, may be skewed. In this article, a threshold longitudinal Tobit quantile regression model is proposed and a computational approach based on alternating direction method of multipliers algorithm is developed for the estimation of parameters in the model. In addition, a random weighting method is employed to estimate the variances of the parameter estimators. The proposed procedures are evaluated through simulation studies and applications to the data from clinical trials.

Measurement and influencing factors of industrial carbon unlocking efficiency under the background of "double carbon"

Based on the panel data of 11 provinces and cities in the Yangtze River Economic Belt of China from 2011 to 2018, the DEA model and Malmquist index were used to calculate the industrial carbon unlocking efficiency of the Yangtze River Economic Belt in a static and dynamic way, and the Tobit model was used to empirically test its influencing factors. The results show that (1) the overall efficiency of industrial carbon unlocking in the Yangtze River Economic Belt is on the rise, but there are regional differences. The efficiency of industrial carbon unlocking in the lower reaches of the Yangtze River is higher than that in the upper and middle reaches. (2) The total factor productivity of industrial carbon unlocking in the Yangtze River Economic Belt has increased steadily on the whole, and technological progress is the main source of growth. (3) Industrial carbon unlocking efficiency is affected by many factors. Environmental regulation and degree of openness have a promoting effect on industrial carbon unlocking efficiency, while government investment and innovation level have a restraining effect on industrial carbon unlocking efficiency.

Consumption of Genetically Modified Food Products and Its Determinants (Case Study: Edible Oil in Mashhad)

In recent decades, the global increase in the demand for food and the increasing growth of the world population has caused an inevitable transition from traditional to advanced agriculture and the use of new technologies in the production of food and agricultural products. One of the new achievements of biotechnology is the production and use of genetically modified plants. The benefits of genetically modified crops can be seen well beyond the farm as well, from helping to conserve natural resources to fighting climate change. Identifying the factors that influence people's acceptance of genetically modified (GM) foods can inform industries and policymakers regarding their innovation trajectories, as well as policy development and implementation. Therefore, the current research evaluates the effect of the marketing mix and other effective factors on the consumption of genetically modified (GM) edible oil in Mashhad, Iran. The required information was collected by completing 390 questionnaires and using the available sampling method in 2022. Factors affecting the probability of consumers making a decision to consume GM edible oil and the consumption amounts of this oil were analyzed through Heckman's two-stage Tobit model using the STATA 16 software package. The results showed that factors affecting the intention of consuming GM edible oils are different from factors affecting the amount of consumption of GM edible oils. Moreover, selected marketing mixes have a significant effect on the amount of consumption of GM edible oils, and therefore, policy-makers can influence the consumption of GM edible oils by using marketing tools. The effect of household monthly income on the consumption of GM edible oil is also negative and significant, which shows that households with higher incomes have less consumption of GM edible oils. Based on the results, trust in the government has a positive and significant effect on the consumption of GM edible oil, so when consumers have trust in their government about GM food products, the consumption of GM edible oil will increase. Therefore, it is suggested that the country's food security authorities gain the trust of consumers by clarifying the production process of GM products and holding scientific debates between the proponents and opponents of the production and consumption of GM food products in order to express the advantages and disadvantages of these products to inform consumers and help them choose between products.

Fiscal decentralization, local government environmental protection preference, and regional green innovation efficiency: evidence from China

Green technological innovation has gained in importance in regional policy making towards gaining competitive advantage and sustainable development. This paper used the data envelopment analysis method to calculate regional green innovation efficiency in China, and empirically tested the effect of fiscal decentralization through Tobit model. The regression results show that the local governments with higher fiscal autonomy would prefer to strengthen environmental protection; thus, the regional green innovation efficiency was improved. After the guidance of relevant national development strategies, these effects became more apparent. Our research provided theoretical support and practical guidance for promoting regional led green innovation, improving environmental quality, achieving carbon neutrality, and promoting the high-quality and sustainable development.

A hierarchical Bayesian analysis for bivariate Weibull distribution under left-censoring scheme

This paper presents a novel approach for analyzing bivariate positive data, taking into account a covariate vector and left-censored observations, by introducing a hierarchical Bayesian analysis. The proposed method assumes marginal Weibull distributions and employs either a usual Weibull likelihood or Weibull-Tobit likelihood approaches. A latent variable or frailty is included in the model to capture the possible correlation between the bivariate responses for the same sampling unit. The posterior summaries of interest are obtained through Markov Chain Monte Carlo methods. To demonstrate the effectiveness of the proposed methodology, we apply it to a bivariate data set from stellar astronomy that includes left-censored observations and covariates. Our results indicate that the new bivariate model approach, which incorporates the latent factor to capture the potential dependence between the two responses of interest, produces accurate inference results. We also compare the two models using the different likelihood approaches (Weibull or Weibull-Tobit likelihoods) in the application. Overall, our findings suggest that the proposed hierarchical Bayesian analysis is a promising approach for analyzing bivariate positive data with left-censored observations and covariate information.

Hierarchy performance assessment of industrial solid waste utilization - tracking resource recycling and utilization centers in China

The massive production and accumulation of industrial solid waste (ISW) have led to environmental pollution and natural resource underutilization. China's efforts to build trial industrial waste resource utilization centers provide strong support for sustainable development. However, these centers and the factors driving ISW utilization have yet to be evaluated. This paper utilizes context-dependent data envelopment analysis models without explicit inputs (DEA-WEI) to evaluate the overall utilization performance of 48 industrial waste resource utilization centers in China from 2018 to 2020. It also builds a Tobit model to assess which indicators and waste types affect overall ISW utilization. The results show overall ISW utilization performance of centers in the sample has improved, with the average value falling from 1.7193 in 2018 to 1.5624 in 2020. However, there are clear regional performance gaps, with East China having the highest utilization performance (1.3113) while the Southwest had the lowest (2.2958). Finally, this paper proposes measures to improve the overall utilization of industrial waste resources based on an analysis of the factors driving solid waste utilization.

The Tobit-Unscented-Kalman-Filter-Based Attitude Estimation Algorithm Using the Star Sensor and Inertial Gyro Combination

For the orbit operation of spacecraft, due to environmental factors, a star sensor installed on the spacecraft must have data censoring, which greatly reduces the attitude determination ability of the traditional combined-attitude-determination algorithm. To address this problem, this paper proposes an algorithm for high-precision attitude estimation based on a Tobit unscented Kalman filter. This is on the basis of establishing the nonlinear state equation of the integrated star sensor and gyroscope navigation system. The measurement update process of the unscented Kalman filter is improved. The Tobit model is used to describe the gyroscope drift when the star sensor fails. The latent measurement values are calculated using the probability statistics, and the measurement error covariance expression is derived. The proposed design is verified via computer simulations. When the star sensor fails for 15 min, the accuracy of the Tobit unscented Kalman filter based on the Tobit model is improved by approximately 90% compared to the unscented Kalman filter. Based on the results, the proposed filter can effectively estimate the error caused by the gyro drift, and the method is effective and feasible, provided there is theoretical support for the engineering practice.

What were the spatiotemporal evolution characteristics and the influencing factors of urban land green use efficiency? A case study of the Yangtze River Economic Belt

China's rapid urbanization has had a tremendous impact on the country's limited land resources, and one of the major issues of green development is how to utilize the limited land resources to maximize social, economic, and environmental advantages. From 2005 to 2019, the super epsilon-based measure model (EBM) was employed to assess the green land use efficiency of 108 prefecture-level and above cities in the Yangtze River Economic Belt (YREB), as well as investigate its spatial and temporal evolution and influential factors. The findings demonstrate that overall, urban land green use efficiency (ULGUE) in the YREB has been ineffective; in terms of city scale, megacities have the highest efficiency, followed by large cities and small and medium-sized cities; and at the regional level, downstream efficiency does have the greatest average value, followed by upstream efficiency and middle efficiency. The results of temporal and spatial evolution reveal that the number of cities with a high ULGUE is increasing in general but that their spatial characteristics are relatively dispersed. Population density, environmental regulation, industrial structure, technology input, and the intensity of urban land investment all have major beneficial effects on ULGUE, whereas urban economic development level and urban land use scale clearly have inhibitory effects. In light of the previous conclusions, some recommendations are made to continuously improve ULGUE.

Impact of carbon lock-in on green economic efficiency: Evidence from Chinese provincial data

Carbon lock-in is a major obstacle to transforming carbon-based energy systems toward carbon peaking and neutralization, affecting the green economy. However, its impacts and paths on green development are unclear, and it is difficult to represent carbon lock-in using a single indicator. This study measures five types of carbon lock-ins and their comprehensive effect using the entropy index of 22 indirect indicators in 31 Chinese provinces during 1995-2021. Moreover, green economic efficiencies are measured using a fuzzy slacks-based model considering undesirable outputs. The panel Tobit models are used to test the impacts of carbon lock-ins on green economic efficiencies and their decompositions. Our results show that provincial carbon lock-ins in China range from 0.20 to 0.80, with notable type and regional differences. Overall carbon lock-in levels are similar, but the severity of different carbon lock-in types varies, with social behavior being the most serious. However, the overall trend of carbon lock-ins is declining. Low pure green economic efficiencies, rather than scale efficiencies, contribute to China's worrisome green economic efficiencies, but they are decreasing and accompanied by regional gaps. Carbon lock-in hinders green development, but a specific analysis is needed for different carbon lock-in types and development phases. It is biased to assume that all carbon lock-ins hinder sustainable development, as some are even necessary. The impacts of carbon lock-in on green economic efficiency depend more on its effect on technology than on scale change. Implementing various measures to unlock carbon and maintaining reasonable levels of carbon lock-in can promote high-quality development. This paper may promote the development of new unlocking CLI measures and sustainable development policies.

How has China's industrial eco-efficiency been improved? Evidence from multi-scale countrywide study

The process of industrialization often causes resource depletion and environmental pollution. To shed light on China's resource use and pollution trends in the context of the country's rapid industrial growth, this study analyzes the eco-efficiency of China's industry from 2000 to 2015. We quantify industrial eco-efficiency (IEE) for China and its provinces using data envelopment analysis (DEA) and analyze potential influencing factors at national and regional levels using Tobit regression. IEE in China and in most provinces shows a clear upward trend with some fluctuations, with national scores increasing from 0.394 to 0.704. There is strong regional disparity, with average IEE scores in eastern provinces (0.840) higher than those in central provinces (0.625), which are in turn higher than those in the northeast (0.537) and west (0.438). We next consider potential drivers. Economic development and foreign direct investment (FDI) are positively associated with IEE but appear to show diminishing returns. Environmental enforcement and market for technology are also positively associated with IEE, as expected. The impact of economic development, industrial sector structure, and investment in research and development (R&D) are modified by the stage of industrialization in each region. Targeted measures that can adjust industry structure, enhance environmental enforcement, attract FDI, and increase R&D investment may help further improve IEE in China.

Identifying the causal effects of long-term exposure to PM2.5 and ground surface ozone on individual medical costs in China-evidence from a representative longitudinal nationwide cohort

BACKGROUND

There is little evidence on whether PM_2.5 and ground surface ozone have consistent effects on increased individual medical costs, and there is a lack of evidence on causality in developing countries.

METHODS

This study utilized balanced panel data from 2014, 2016, and 2018 waves of the Chinese Family Panel Study. The Tobit model was developed within a counterfactual causal inference framework, combined with a correlated random effects and control function approach (Tobit-CRE-CF), to explore the causal relationship between long-term exposure to air pollution and medical costs. We also explored whether different air pollutants exhibit comparable effects.

RESULTS

This study encompassed 8928 participants and assessed various benchmark models, highlighting the potential biases from failing to account for air pollution endogeneity or overlooking respondents without medical costs. Using the Tobit-CRE-CF model, significant effects of air pollutants on increased individual medical costs were identified. Specifically, margin effects for PM_2.5 and ground-level ozone signifying that a unit increase in PM_2.5 and ground-level ozone results in increased total medical costs of 199.144 and 75.145 RMB for individuals who incurred fees in the previous year, respectively.

CONCLUSIONS

The results imply that long-term exposure to air pollutants contributes to increased medical costs for individuals, offering valuable insights for policymakers aiming to mitigate air pollution's consequences.

Analysis of financial support efficiency and influencing factors of listed seed companies from the perspective of energy consumption and carbon emissions

The seed industry has a prominent role in strengthening ecological stability and national food security as it provides the basic ground for agriculture sector. In the current research, the effectiveness of financial support provided to listed seed enterprises and its influencing factors from the perspectives of energy consumption and carbon emissions are examined using a three-stage DEA-Tobit model. The dataset for the underlined study variables mainly comes from the financial data published by 32 listed seed enterprises and the China Energy Statistical Yearbook from 2016 to 2021. In order to make the results more accurate, the influence of external environmental factors such as economic development level, total energy consumption, and total carbon emission on listed seed enterprises are excluded. The results revealed that the mean value of financial support efficiency of listed seed enterprises increased significantly after excluding the influence of external environmental and random factors. External environmental factors such as regional energy consumption and carbon dioxide emission played an important role in the process of the financial system supporting the development of listed seed enterprises. The development of some listed seed enterprises with high financial support efficiency came at the cost of high local carbon dioxide emission and high energy consumption. Internal factors such as operating profit, equity concentration, financial structure, and enterprise size are the key intra-firm factors that affect the efficiency of financial support for listed seed enterprises. Thus, it is suggested that enterprises must pay attention to the environmental performance to reach a win-win situation in reducing and improving the energy consumption and financial performance, respectively. Similarly, the improvement of energy use efficiency through endogenous and external innovation should be prioritized to achieve sustainable economic development.

Digital economy and industrial energy efficiency performance: evidence from the city of the Yangtze River Delta in China

Industry dominates energy consumption and carbon emissions in China, and industrial energy efficiency is critical for the achievement of energy transformation and carbon emission reduction. With the rapid development of the digital economy, its impact on energy efficiency is gradually emerging, and it is necessary to clarify the influencing mechanism on industrial energy efficiency. Based on the panel data of industrial sectors in 41 cities in the Yangtze River Delta from 2011 to 2019, the main objectives of this study are to more accurately measure the industrial total factor energy efficiency in each city by using the Super-Dynamic-SBM model. It analyses the influence mechanism of the digital economy and other influencing factors on industrial total factor energy efficiency with different methods. The research results indicate that, first, the total factor energy efficiency of the industrial sector in the Yangtze River Delta urban agglomeration generally showed a steady upward trend. Second, the digital economy and environmental regulation play a significant role in promoting total factor energy efficiency. In addition, industrial energy efficiency and the digital economy show an inverted "U" shaped relationship. With the improvement of the digital economy, its marginal contribution to total factor energy efficiency gradually weakens. Finally, technological progress is an important transmission channel for the impact of the digital economy on total factor energy efficiency.

Impact of the development of information society on healthcare efficiency: Empirical evidence from 31 Chinese provinces

The development of information society has deeply changed the style of the healthcare service delivery and medical information access. This study aims to investigate how the information society development affects the efficiency of healthcare system in China, and explore provincial disparities in the impact. Based on the two-stage Data Envelopment Analysis (DEA) framework, this paper uses a panel data from 31 Chinese provinces from 2014 to 2017 to estimate efficiency of healthcare service and analyze the influence of the development of information society on efficiency. With the information society index (ISI) increased from 0.423 to 0.488 during the sample period, the healthcare efficiency experienced a slight decrease from 0.892 to 0.869. Moreover, the pure technical efficiency (PTE) is much lower than the scale efficiency (SE), and thus is the key to enhance the overall technical efficiency (TE). The time-fixed Tobit regression analysis suggests that information society development leads to a significant increase in PTE, but results in a decrease in SE, and therefore has little effect on TE. Further analysis reveals that the impact differs sharply between low-efficiency and high-efficiency provinces. For the low-efficiency provinces, the TE increases significantly with the development of the information society, mainly due to a considerable increase in PTE. In contrast, the TE decreases for the high-efficiency provinces, mainly caused by a decrease in SE. This paper highlights the importance of information infrastructure investment in healthcare system and the application of emerging information technologies to breakout the time and space boundaries of healthcare services in improving overall efficiency. In inefficient provinces, it is also necessary to properly control the growth of healthcare inputs.