A Cross-Sectional Analysis of Employment Returns to Education and Health Status in China: Moderating Role of Gender

Urbanization, rural energy-poverty, and carbon emission: unveiling the pollution halo effect in 48 BRI countries

The Belt and Road Initiative (BRI) is a significant economic development strategy directed by China. Its primary objective is to establish connectivity across a vast region encompassing over 70 countries in Asia, Europe, and Africa. This endeavor significantly impacts worldwide development, economic advancement, and environmental sustainability. Nevertheless, insufficient pertinent evidence exists when exploring the correlation between urbanization, rural energy poverty (Rural_EP), and carbon emissions (CO2_Em) in the BRI region. The present study examines panel data encompassing 48 countries participating in BRI from 2001 to 2020. This research addresses existing gaps by employing the System-GMM and Driscoll and Kraay Standard Error (DKSE) models to investigate factors influencing CO2_Em. The findings indicate that the presence of energy poverty in rural areas is associated with higher levels of CO2_Em, while urbanization has a mitigating effect on such emissions. Furthermore, adopting production methods and environmentally sustainable technologies by foreign corporations leads to a decrease in CO2_Em, thereby providing evidence of a pollution halo effect in BRI. Moreover, economic growth and industrialization have detrimental environmental consequences, primarily through the amplification of CO2_Em. Based on the empirical evidence, the study proposes policy measures that advocate for promoting renewable energy sources, adopting sustainable urban development practices, implementing energy conservation strategies, and establishing carbon pricing mechanisms.

How Do R&D and Renewable Energy Consumption Lead to Carbon Neutrality? Evidence from G-7 Economies

The discussion about whether research and development and advanced energy structure can efficiently control pollution has gained the consideration of researchers across the globe. However, there is a lack of enough empirical and theoretical evidence to support this phenomenon. To offer support of empirical evidence along with theoretical mechanism, we examine the net Impact of research and development (R&D) and renewable energy consumption (RENG) on CO2E utilizing panel data from G-7 economies for 1990-2020. Moreover, this study investigates the controlling role of economic growth and nonrenewable energy consumption (NRENG) in the R&D-CO2E models. The results obtained from the CS-ARDL panel approach verified a long-run and short-run relationship between R&D, RENG, economic growth, NRENG, and CO2E. Short- and long-run empirical results suggest that R&D and RENG improve environmental stability by decreasing CO2E, while economic growth and NRENG increase CO2E. Particularly, long-run R&D and RENG reduce CO2E with the effect of -0.091 and -0.101, respectively, while in the short run, they reduce CO2E with the effect of -0.084 and -0.094, respectively. Likewise, the 0.650% (long run) and 0.700% (short-run) increase in CO2E is due to economic growth, while the 0.138% (long run) and 0.136% (short run) upsurge in CO2E is due to an increase in NRENG. The findings obtained from the CS-ARDL model were also verified by the AMG model, while D-H non-causality approach was applied to check the pair-wise relationship among variables. The D-H causal relationship revealed that policies to focus on R&D, economic growth, and NRENG explain variation in CO2E but not vice versa. Furthermore, policies considering RENG and human capital can also affect CO2E and vice versa, meaning there is a round effect between the variables. All this indication may guide the concerned authorities to devise comprehensive policies that are helpful to environmental stability and in line with CO2E reduction.

Health, Education, and Economic Well-Being in China: How Do Human Capital and Social Interaction Influence Economic Returns

In developing countries, it is generally believed that a good health status and education (human capital) bring economic well-being and benefits. Some researchers have found that there are overall financial returns and income premiums correlated with human capital because of its excellent and higher ability. Due to different views and a lack of consensus, the role of human capital is still ambiguous and poorly understood. This study investigates the economic returns of health status, education level, and social interaction, that is, whether and how human capital and social interaction affect employment and income premiums. Using the Chinese General Social Survey (CGSS) for specification bias, we used the instrumental variable (IV) approach to specify the endogeneity and interaction effect in order to identify the impact and economic returns of human capital and social interaction on the values of other control and observed variables. However, we show that an individual with strong and higher human capital positively affects economic returns, but the variability of these estimates differs across estimators. Being more socially interactive is regarded as a type of social interaction but as not human capital in the labor market; thus, the empirical findings of this study reflect social stability and that the economic well-being of socially active individuals is an advantaged situation. Furthermore, men with substantial human capital and social interaction are in a more advantaged position compared to women with similar abilities.

How do clean fuels and technology-based energy poverty affect carbon emissions? New evidence from eighteen developing countries

Clean fuels and technology-based energy is an essential source to achieve sustainable economic growth and development. Therefore, the relationship between all types of poverty and other socioeconomic indicators has been studied extensively; nevertheless, clean fuels and technology-based energy poverty, adjusted for carbon emissions, has not been studied. The current study examines the impact of clean fuels and technology-based energy poverty on carbon emissions (Co2e). Using System-Generalized Method of Movement (SGMM) estimators, this study utilized panel data from eighteen developing countries in Asia from 2006 to 2017. The empirical findings obtained from econometric model suggest the presence of clean fuels and technology-based energy poverty and its curse on environment, i.e., energy poverty positively affects Co2e growth in Asian developing countries. Furthermore, economic growth (GDP), trade, and population are also positively associated with Co2e growth and negatively affect environmental quality. Based on the empirical findings of the current study, we recommend robust policy implications that the governments of targeted countries should invest more to increase clean fuels and technologies.

Health Risk, Income Effect, and the Stability of Farmers' Poverty Alleviation in Deep Poverty Areas: A Case Study of S-County in Qinba Mountain Area

Health status and income level are both important factors in reducing poverty and accomplishing sustainable development in deep poverty areas of China. Therefore, the purpose of this study is to provide policy support for the sustainable poverty alleviation of farmers by analyzing the net effect of health risk on Farmers' income poverty and its impact mechanism. Based on the data of more than 199,000 farmers, this study uses the Difference in Difference (DID) model to empirically analyze the effect of health-risk on farmers' income poverty. The empirical findings obtained from DID model show that health risk has a significant and positive impact on income poverty, where the impact of disability is higher. Furthermore, the mechanism shows that the impact of health risks on income poverty is mainly influenced by farmers' off-farm working choices and time. The heterogeneity analysis shows that the health risk significantly impacts non-vulnerable farmers' poverty. With outdated healthcare facilities in poverty-stricken areas, people are more likely to fall into income poverty. Therefore, the study concludes that establishing an effective long-term mechanism of health risk prevention is essential to improving the endogenous development power of poor farmers and decreasing income poverty.

How does economic complexity affect ecological footprint in G-7 economies: the role of renewable and non-renewable energy consumptions and testing EKC hypothesis

The discussion concerning whether and how economic complexity (ECI) affects ecological footprint (EFP) has gained researchers' consideration, while there are slight empirical evidence to support the subject matter. In the support of theoretical argument, this study provides empirical evidence by investigating the impact of ECI on EFP along with the role of disaggregated energy consumptions by using a panel dataset of G-7 economies between 1996 and 2019. To this end, we applied panel techniques of Fully-Modify OLS and Dynamic-OLS models for cointegration analysis. The results obtained from Fully-Modify OLS and Dynamic-OLS models reveal that ECI deteriorates environmental quality by increasing EFP, while renewable energy reduces ecological pollution by decreasing EFP. In addition, the increasing demand for non-renewable energy and economic growth both degrades environmental quality in G-7 countries. More interestingly, the non-linear (ECI²) relationship between ECI and EFP confirms a U-shaped association (EKC hypothesis), which suggests that after achieving a certain threshold level, economic complexity mitigates environmental degradation in G-7 economies. The empirical results also suggest that other control variables such as population growth, inflation rate, foreign direct investment, and total trade intensity lead to environmental degradation by increasing ecological footprint. Based on empirical results, the following important policy implications are drawn; first, G-7 economies should speed up the level of economic complexity along with renewable energy consumption to protect environmental quality and maintain sustainable growth and development. Secondly, the governments of G-7 countries should introduce greener technologies and promote production that are environmental friendly for drastic reduction in environmental unsustainability.

Development trend of primary healthcare after health reform in China: a longitudinal observational study

OBJECTIVES

Reconstructing the primary healthcare system is the focus of the new round of Chinese health reform. Nevertheless, there have been few studies focusing on the strengthening of primary healthcare in Chinese health system.

DESIGN

This study was a longitudinal observational study.

PRIMARY AND SECONDARY OUTCOME MEASURES

The data of this study came from China Health Statistical Yearbook (2009-2018). We evaluated the development of primary healthcare based on the absolute values of health resources allocation and health service provision and evaluated the status of primary healthcare throughout the health system based on the composition ratios of the indicators across the health system. The Cochran-Armitage trend test and linear trend test were used to identify the indicators' trends over time.

RESULTS

From 2009 to 2018, the amounts of health resources allocation and health service provision of Chinese primary healthcare institutions showed a significant upward trend (p<0.001). However, compared with the indicators in 2009, excepting that the proportion of grants from the government in the whole health system has an upward trend, the proportions of other indicators had an escalating trend in 2018 by 3.66% for practicing (assistant) physicians, by 2.69% for nurses, by 3.99% for total revenues, by 5.87% for beds, by 8.39% for outpatient visits.

CONCLUSION

The primary healthcare system has developed rapidly, but its development speed lagged behind the entire health system, resulting in the weakening of its actual functions, which is not in line with the goal of health reform. The government should be more aware of the importance of primary healthcare at all levels of local governments and ensure adequate financial input.

Nursing Interns' Attitudes Toward, Preferences for, and Use of Diabetes Virtual Simulation Teaching Applications in China: National Web-Based Survey

BACKGROUND

Diabetes has placed heavy social and economic burdens on society and families worldwide. Insufficient knowledge and training of frontline medical staff, such as nurses, interns, and residents, may lead to an increase in acute and chronic complications among patients with diabetes. However, interns have insufficient knowledge about diabetes management. The factors that affect interns' current level of diabetes-related knowledge are still unclear. Therefore, understanding the behavioral intentions of interns is essential to supporting the development and promotion of the use of virtual simulation teaching applications.

OBJECTIVE

This study aimed to identify the determinants of nursing interns' intentions to use simulation-based education applications.

METHODS

From December 1, 2020, to February 28, 2021, the web-based survey tool Sojump (Changsha Xingxin Information Technology Co) was used to survey nursing interns in hospitals across China. Two survey links were sent to 37 partner schools in 23 major cities in China, and they were disseminated through participants' WeChat networks. Multiple regression analysis was used to determine the association between demographic information and basic disease information and the use of the application for treating adult patients.

RESULTS

Overall, 883 nursing interns from 23 provinces in China responded to the survey. Among them, the virtual simulation utilization rate was 35.6% (314/883) and the awareness rate was 10.2% (90/883). In addition, among the interns, only 10.2% (90/883) correctly understood the concept of virtual simulation, and most of them (793/883, 89.8%) believed that scenario-simulation training or the use of models for teaching are all the same. Multiple regression analysis showed that the educational level, independent learning ability, and professional identity of the interns were related to use of the application (P<.05). Skills and knowledge that the interns most wanted to acquire included the treatment of hypoglycemia (626/883, 70.9%), functional test simulation (610/883, 69.1%), and blood glucose monitoring technology (485/883, 54.9%). A total of 60.5% (534/883) of the interns wanted to acquire clinical thinking skills, while 16.0% (141/883) wanted to acquire operational skills. Nursing trainees believed that the greatest obstacles to virtual simulation included limited time (280/883, 31.7%), the degree of simulation (129/883, 14.6%), the demand for satisfaction (108/883, 12.2%), and test scores (66/883, 7.5%).

CONCLUSIONS

The understanding and usage rate of diabetes virtual simulation teaching applications by Chinese nursing interns is very low. However, they have high requirements regarding this teaching method. Conducting high-quality randomized controlled trials and designing applications that are suitable for the needs of different nurse trainees will increase students' interest in learning and help improve diabetes knowledge among nursing interns.