A prospective health economic evaluation to determine the productivity loss due to premature mortality from oral cancer in India.

INTRODUCTION: India contributes two-thirds of the global mortality due to oral cancer and has a younger population at risk. The societal costs of this premature mortality are barely discussed. METHODS: Using the human capital approach, we aimed to estimate the productivity lost due to premature mortality, valued using individual socioeconomic data, related to oral cancer in India. A bottom-up approach was used to prospectively collect data of 100 consecutive patients with oral cancer treated between 2019 and 2020, with a follow-up of 36 months. RESULTS: The disease-specific survival for early and advanced stage was 85% and 70%, with a median age of 47 years. With 671 years lost prematurely, the loss of productivity was $41 900/early and $96 044/advanced stage. Based on population level rates, the total cost of premature mortality was $5.6 billion, representing 0.18% of GDP. CONCLUSION: India needs to implement tailored strategies to reduce the economic burden from premature mortality.

From service design thinking to the third generation of activity theory: a new model for designing AI-based decision-support systems.

Introduction: The rise of Artificial Intelligence (AI), particularly machine learning, has brought a significant transformation in decision-making (DM) processes within organizations, with AI gradually assuming responsibilities that were traditionally performed by humans. However, as shown by recent findings, the acceptance of AI-based solutions in DM remains a concern as individuals still strongly prefer human intervention. This resistance can be attributed to psychological factors and other trust-related issues. To address these challenges, recent studies show that practical guidelines for user-centered design of AI are needed to promote justified trust in AI-based systems. Methods and results: To this aim, our study bridges Service Design Thinking and the third generation of Activity Theory to create a model which serves as a set of practical guidelines for the user centered design of Multi-Actor AI-based DSS. This model is created through the qualitative study of human activity as a unit of analysis. Nevertheless, it holds the potential for further enhancement through the application of quantitative methods to explore its diverse dimensions more extensively. As an illustrative example, we used a case study in the field of human capital investments, with a particular focus on organizational development, which involves managers, professionals, coaches and other significant actors. As a result, the qualitative methodology employed in our study can be characterized as a "pre-quantitative" investigation. Discussion: This framework aims at locating the contribution of AI in complex human activity and identifying the potential role of quantitative data in it.

Spatial and emotional distances in parent-child relationships: Impacts on human capital development in rural Chinese boarding children.

BACKGROUND: The policy of merging remote rural elementary schools into centralized villages has led to the emergence of boarding schools as an essential means of providing compulsory education in rural areas of China. As boarding children reside in schools for extended periods, parents' influence on their human capital development is inevitably specificity. The development of rural boarding children is a serious social issue in China, and parent-child distance plays a crucial role in affecting the development of children's human capital. OBJECTIVE: While previous studies have focused on the relationship between parental absence and the development of human capital in rural boarding children, this study examines the effects of both spatial and emotional distance between parents and children on the human capital of rural boarding children. PARTICIPANTS AND SETTING: A stratified, multi-stage probabilities proportional to size (PPS) sampling method was used, and self-report questionnaires were completed by 2397 rural boarding children (54.2 % males; ages 12 to 18, M = 14.66, SD = 1.30). METHODS: Children's background, family, and school and teacher characteristics were used as control variables. An OLS regression model was used to assess the effects of parent-child spatial and emotional distance on the human capital of rural boarding children, and a CMP-OLS regression model was used to address endogeneity using parents' self-assessed family economic conditions as instrumental variables. RESULTS: Parent-child spatial distance had a significant positive effect (p < 0.05, p < 0.05), and emotional distance had a significant negative effect (p < 0.05, p < 0.01) on the cognitive and non-cognitive abilities development of rural boarding children. Living with grandparents heightened the negative effect on non-cognitive abilities development. CONCLUSIONS: The findings of this study strengthen the link between parent-child distance and rural boarding children and the moderating impact of living with grandparents on the effect of parent-child distance on rural boarding children's human capital providing new insights for promoting the development of rural boarding children. It also highlights the detrimental effects of emotional neglect on rural boarding children's development. This is important for realizing China's rural revitalization strategy and the healthy development of disadvantaged children in rural areas.

Trade openness, human capital, natural resource, and carbon emission nexus: a CS-ARDL assessment for Central Asian economies.

There is a call for global efforts to preserve the ecological systems that can sustain economies and people's lives. However, carbon emission (CEM) threatens the sustainability of humanity and ecological systems. This analysis looked into the influence of energy use (ERU), human capital (HCI), trade openness (TOP), natural resource (NRR), population, and economic growth (ENG) on CEM. The paper gathered panel data from the Central Asia region from 1990 to 2020. The CS-ARDL was applied to establish the long-term interaction among the indicators. The paper's findings indicated the presence of the environmental Kuznets curve (EKC) in the Central Asia regions. Also, the empirical evidence highlighted that energy use, natural resources, and trade openness cause higher levels of CEM. However, the research verified that CEM can be improved through human capital and urban population growth. The study also found that HCI moderates the interaction between NRR and CEM. The causality assessment indicated a one-way interplay between ENG, ERU, NRR, and CEM. The study proposes that to support ecological stability in these regions, policy-makers should concentrate on developing human capital, investing in renewable energy sources, and utilizing contemporary technologies to harness natural resources in the economies of Central Asia.

Examining the dynamics between economic development, tourism, renewable energy and life expectancy in the Nordic economies.

As the world struggles with pressing issues like climate change and sustainable development, affecting health outcomes and environmental quality, the Nordic regionsare at the forefront of major global challenges. This paper investigates the role of human capital, renewable energy use, tourism, natural resources, and economic growth in shaping life in the Nordic region i.e., Denmark, Norway, Sweden, Finland, and Iceland).Utilizing panel data spanning from 1990 to 2020, the Driscoll and Kraay standard error (DSK) technique is employed to analyze this intricate interplay. The study reveals that in the Nordic context, sustainable economic growth, bolstered by investments in human capital and the widespread acceptance of renewable energy sources, has been positively associated with increased life expectancies. Furthermore, prudent management of natural resources has helped mitigate adverse health effects related to depletion, maintaining environmental and public health standards. The thriving tourism industry has also been shown to influence lifespan in this region positively. On the contrary, the empirical finding contended that an adverse correlation exists between carbon emissions and LEX. This research underscores the importance of a comprehensive and balanced approach that considers economic development, sustainable development, and public health in pursuing longer and healthier lives, providing valuable insights for policymakers and regions seeking to replicate these positive outcomes.The findings of this study are both conceptually reliable and empirically robust, providing important insights for the formulation of environmental and health policy.

Intelligence and its effects on environmental decline: A worldwide analysis.

The research investigates the relationship between intelligence quotient (IQ) and environmental degradation, aiming to understand how cognitive abilities influence environmental outcomes across different nations and time periods. The objective is to examine the impact of intelligence quotient (IQ) on environmental indicators such as carbon emissions, ecological demand, and the Environmental Kuznets Curve (EKC), seeking insights to inform environmental policy and stewardship. The study utilizes statistical techniques including Ordinary Least Squares (OLS), Two Stage Least Squares (2SLS), and Iteratively Weighted Least Squares (IWLS) to analyze data from 147 nations over the years 2000-2017. These methods are applied to explore the relationship between IQ and environmental metrics while considering other relevant variables. The findings reveal unexpected positive associations between human intelligence quotient and carbon emissions, as well as ecological demand, challenging conventional notions of "delay discounting." Additionally, variations in the Environmental Kuznets Curve (EKC) hypothesis are identified across different pollutants, highlighting the roles of governance and international commitments in mitigating emissions. The study concludes by advocating for the adoption of a "delay discounting culture" to address environmental challenges effectively. It underscores the complex interactions between intelligence, governance, and population dynamics in shaping environmental outcomes, emphasizing the need for targeted policies to achieve sustainability objectives.

Estimating a Theoretically Consistent Human Capital Production Function With an Application to Head Start.

This article describes a conceptual and empirical approach for estimating a human capital production function of child development that incorporates mother- or child-fixed effects. The use of mother- or child-fixed effects is common in this applied economics literature, but its application is often inconsistent with human capital theory. We outline the problem and demonstrate its empirical importance with an analysis of the effect of Head Start and preschool on child and adult outcomes. The empirical specification we develop has broad implications for a variety of applied microeconomic analyses beyond our specific application. Results of our analysis indicate that attending Head Start or preschool had no economically or statistically significant effect on child or adult outcomes.

Household Decision-Making Choices: Investment in Children's Education or Self-Consumption.

Analyzing the sustainable decision-making mechanism between household consumption and education investment can theoretically develop education. This study uses the continuous-time utility model to demonstrate the independent characteristics of consumption and education investment, as well as the principle of decision incompatibility in the decision-making process of the utility maximization problem. Then, we establish a three-phase logarithmic utility model to obtain the intertemporal decision-making path of a family. The analysis shows that the investment allocation ratio between the two phases depends on the expected and discounted level of the offsprings' abilities, while the total investment level is related to parental altruism. When parents, with foresight, factor in prospective transfer payments from progeny, the optimal decision is to maximize their children's ultimate human capital within a given total investment. Education investment not only squeezes out consumption but also promotes consumption in various periods due to future transfer payments. The decision-making process of three typical growth stages indicates that as offspring mature and their human capital increases, parents' willingness to invest in education decreases while self-consumption escalates. This study provides a new perspective and theoretical basis for studying household education expenditure, motivation, and related policy formulation.

Linking to the development of economic growth with digital financial inclusion and supply chain management in China.

Much research demonstrates the positive effects of financial inclusion and digital finance on expansion. Supply chains that can be relied upon are essential to national productivity and economic development. This study uses panel data from 2007 to 2022 covering 27 provinces in China to study the results of widespread access to digital financial services and supply chain management on regional economic growth using the instrumental variable approach (fixed effect model). In contrast to earlier research, this study employs an alternative measure of access to digital financial services utilization and digitalization. The data demonstrates that digital financial inclusion and supply chain management have a major impact on the development of the provincial economies in China. Based on the results of this research, we suggest increasing digital financial inclusion and bolstering human capital development to stimulate economic expansion. This essay makes a theoretical advancement in studying digital technology's widespread adoption of financial services by providing a comprehensive critical review and a fresh angle on the nuts and bolts of digital money and universal banking. Boosting institutional quality and governance are two more paths that authorities can take to stimulate economic expansion in the China area, and the results show how important these measures are for achieving this goal.

The role of human capital and stress for cost awareness in the healthcare system: a survey among German hospital physicians.

BACKGROUND: Germany has the highest per capita health care spending among EU member states, but its hospitals face pressure to generate profits independently due to the government's withdrawal of investment cost coverage. The diagnosis related groups (DRG) payment system was implemented to address the cost issue, challenging hospital physicians to provide services within predefined prices and an economic target corridor to reduce costs. This study examines the extent of cost awareness among medical personnel in German hospitals and its influencing factors. METHODS: We developed an online survey in which participants across all specialties in hospitals estimated the prices in euros of four common interventions and answered questions about their human capital and perceived stress on the workplace. As a measure of cost awareness, we used the probability of estimating the prices correctly within a reasonable margin. We employed logit logistic regression estimators to identify influencing factors in a sample of 86 participants. RESULTS: The results revealed that most of the respondents were unaware of the costs of common interventions. General human capital, acquired through prior education, and job-specific human capital had no influence on cost awareness, whereas domain-specific human capital, that is, gaining economic knowledge based on self-interest, had a positive nonlinear effect on cost awareness. Furthermore, an increased stress level negatively influenced cost awareness. CONCLUSIONS: This paper is the first of its kind for the German health care sector that contributes responses to the question whether health care professionals in German hospitals have cost awareness and if not, what reasons lie behind this lack of knowledge. Our findings show that the cost awareness desired by the introduction of the DRG system has yet to be achieved by medical personnel.

Health and Economic Growth: Reconciling the Micro and Macro Evidence.

Economists use micro-based and macro-based approaches to assess the macroeconomic return to population health. The macro-based approach tends to yield estimates that are either negative and close to zero or positive and an order of magnitude larger than the range of estimates derived from the micro-based approach. This presents a micro-macro puzzle regarding the macroeconomic return to health. We reconcile the two approaches by controlling for the indirect effects of health on income per capita, which macro-based approaches usually include but micro-based approaches deliberately omit when isolating the direct income effects of health. Our results show that the macroeconomic return to health lies in the range of plausible microeconomic estimates, demonstrating that both approaches are in fact consistent with one another.

Do renewable energy and human capital facilitate the improvement of environmental quality in the United States? A new perspective on environmental issues with the load capacity factor.

Recently, countries have been making intensive efforts to alleviate the burden on the environment and to make environmental conditions sustainable. In this context, our study aims to investigate the long-term impact of renewable energy consumption (REC) and human capital (HC) by considering the load capacity factor (LCF). We also investigate the long-term impact of economic growth (Y) and non-renewable energy consumption (NREC) on the LCF. In this context, we analyze annual data for the U.S. for the period 1965-2018 using the newly developed augmented ARDL (AARDL) approach. The long-term empirical results show the following. i) Increases in Y negatively affect LCF and deteriorate environmental quality. ii) Increases in NREC negatively affect LCF and accelerate the deterioration of environmental quality. iii) REC has no significant impact on environmental quality. iv) Increases in HC support the improvement of environmental quality. The empirical results show that contrary to expectations, renewable energy consumption does not have a significant impact on environmental quality in the U.S., whereas human capital is an important factor in improving environmental quality. In this context, US policymakers should pave the way for more investment in eco-friendly renewable energy investments and human capital to establish sustainable environmental quality. Policymakers should also take steps to reduce the use of fossil fuels.

Early Weight Status and Human Capital in Adulthood: A 32-Year Follow-Up of the 1970 British Cohort Study.

Objectives: To prospectively evaluate the effects of early weight status (childhood and adolescence) and changes in obesity status on human capital in adulthood. Methods: We employed data from the 1970 Birth Cohort Study in the United Kingdom. Data on height and weight during childhood and adolescence, human capital variables in adulthood were collected from 2,444 participants. Human capital includes cognitive ability, non-cognitive skill, educational attainment and health status. Data were analyzed through linear regression and logistic regression models. Results: Our results showed that obesity during adolescence was negatively associated with cognitive ability (ß = -0.83, p < 0.01), educational attainment (ß = -0.49, p < 0.01), and some health outcomes; and that underweight in childhood also adversely affected educational attainment in females (ß = -0.66, p < 0.05). In terms of changes in obesity status, becoming obese in adolescence negatively affected cognitive ability (ß = -1.18, p < 0.01), educational attainment (ß = -0.62, p < 0.05) and some health outcomes, remaining obese was associated with all adverse health outcomes. Conclusion: Our results suggest that obesity during adolescence negatively affects a range of human capital outcomes in adulthood, and adolescence is a critical period during which early obesity affects adult human capital.

An environmental perspective of energy consumption, overpopulation, and human capital barriers in South Asia.

Prior literature is substantive in highlighting the nexus between pollutant and socio-economic predictors; however, the role of human interaction has not been sufficiently explored. Thus, the present study examines the validity of the environmental Kuznets Curve (EKC) hypothesis in the presence of energy consumption, overpopulation, and human capital index in five South Asian countries. It employs fixed effects, random effects, and dynamic panel causality techniques with a set of panel data from 1972 to 2021. The baseline results validate the existence of the EKC hypothesis in the recipient panel. Nevertheless, the findings reveal that energy consumption and population density have positive effects, while human capital has negative impacts on CO2 emissions. Furthermore, the study observes that energy consumption and per capita GDP have a significant causal link with CO2 emissions, whereas CO2 emissions are evident to have causality with population density and human capital index. The results are robust and suggest that the consolidation of an effective regulatory framework and technological improvements are substantial measures to improve environmental quality in South Asia. Moreover, allocating sufficient resources to uplift contemporary educational and health status would be imperative to improving environmental quality as aspired to by the Paris Agreement.

Minimum wage standard adjustment and employment: Heterogeneity effects on the human capital investment.

Considerable debate has arisen around the potential effects of increasing the minimum wage on employment. This study aims to analyze the impact of changes in China's minimum wage standard on employment. The research utilises the canonical model method and constructs a regression model based on standard labor economics theory. The analysis is conducted using sample data from Chinese industrial enterprises between 2000 and 2007. Regression analysis is performed by categorizing enterprises based on their level of human capital investment. The findings indicate that minimum wage increases have a non-linear impact on employment, when seen from the standpoint of human capital investment. When the level of human capital investment is low, an increase in the minimum wage standard leads to a decrease in employment; when the level of human capital investment is high, an increase in the minimum wage standard leads to an increase in employment. According to the findings, the reason for this is that, investments in human capital can improve business profitability, increase worker marginal productivity, and increase labor demand. Similarly, the employment effect of a change in the minimum wage is positive in regions with high levels of human capital investment due to the externality effect of human capital. Adjustments to the minimum wage have a negative impact on employment in areas of the country with low levels of human capital investment. This demonstrates that changing the minimum wage does not result in a simple increase or decrease in total employment. The level of investment in human capital within the organization and the region is an important factor in determining the type and magnitude of the impact.

How do information and communication technology, human capital and renewable energy affect CO2 emission; New insights from BRI countries.

If nations want to attain sustainable development with the exponential growth of information and communication technology (ICT) around the world, they must understand the connection between ICT and carbon emissions. Therefore, this study has used panel data from 64 ''Belt and Road Initiative economies between 2000 and 2021 while finding the impact of ICT, renewable energy consumption (REC), human capital (HC) and economic growth (EG) on CO2 emissions. This study employs the Augmented Mean Group (AMG) estimator, Mean Group (MG) estimator and the Dumitrescu-Hurlin panel causality. The findings indicate that the use of ICT, HC and the REC are inversely related to CO2 emissions, whereas EG is positively associated to CO2 emissions and hence poses a danger to environmental sustainability. In addition, the interaction term of EG with ICT, REC and HC has negative impact on CO2 emissions in BRI economies. Intriguingly, the results reveal that ICT and CO2 emissions has inverted U-shape relationship in BRI economies. Furthermore, the causality results show that ICT, REC, and human capital are all cause and effect linkages that affect CO2 emissions in both directions. In order to reduce energy utilization and boost economic growth, the findings stress the importance of implementing cutting-edge ICT and REC in the industrial sector.

Can environmental protection tax force enterprises to improve green technology innovation?

The introduction of an environmental protection tax enables a smooth shift from the sewerage charge system to the environmental protection tax scheme. This, in turn, promotes a more sustainable development of enterprise growth, emphasizing eco-friendliness. This is of immense importance in advancing environmentally aware practices and sustainability. Based on data collected from A-share listed companies in Shanghai and Shenzhen from 2014 to 2021, this paper investigates the influence of environmental protection taxes on the advancement of green technology and the underlying mechanisms. Taking the execution of the Environmental Protection Tax Law in 2018 as a quasi-natural experiment, a double-difference model is employed to examine the causal relationship between environmental protection taxes and the adoption of green technology by companies. The findings indicate that the introduction of an environmental tax could markedly enhance the extent of green technological innovation within corporations. The evidence arising from the testing mechanism implies that such a tax can encourage firms to boost their investments in research and development, upgrade their innovative human capital, and mitigate financing limitations. The study found that there is heterogeneity in the promotion effect of the environmental protection tax on the green technological innovation of businesses in different regions and provinces with varying tax burdens and types of equity capital. Further research shows that the environmental protection tax has a greater impact on the promotion of utility model patent applications for green technology innovation. This paper presents empirical evidence to support further enhancement of the environmental protection tax system. It recommends designing the environmental protection tax policy with consideration for enterprises and local conditions and bolstering the system's capacity for guiding and stimulating enterprises' green development.

Decoding the green supply chain: Education as the key to economic growth and sustainability.

The value of environmental safeguarding is rising in both private and public spheres. What is meant by the term "green supply chain management" (GSCM)? It is minimizing the negative effects of a company's operations on the natural world. Particularly in the research and academic disciplines of the expanding economy of the China region, the concept of the intersection of green supply chain management and sustainable development is dissected at a foundational level. However, there has been little attention paid to how GSCM, GHC, environmental performance, and economic performance all relate to one another. This study fills that void in the literature by giving hard data to encourage businesses in the China area to adopt GHC (green human capital) and SCM (sustainable supply chain management) in order to significantly improve their environmental and economic outcomes. To better understand the interplay between these ideas, we constructed a conceptual framework. The information was gathered using a survey consisting of questionnaires. Manufacturing companies from ten (10) different areas in China provided the 470 responses. The information was analyzed using structural equation modeling (SEM). Research shows that green human capital and green supply chain management have a beneficial influence on economic performance but no discernible effect on environmental outcomes. The results also demonstrate that green supply chain management is an effective act as a mediator between environmental performance and economic performance, with a beneficial effect on both. An initial conclusion may be made that bettering the green human capital stock was more important for China's green economy's growth than bettering the human capital structure. Research like this helps fill out the picture of the green economy and informs policy decisions at the national level.

The impact of digital infrastructure on provincial green innovation efficiency-empirical evidence from China.

In the epoch of the digital economy, technological innovation and energy conservation are significantly facilitated by digital infrastructure, leading to substantial improvements in green innovation efficiency at the provincial level. This study employed the feasible generalized least square (FGLS) method to examine the effects of digital infrastructure on the green innovation efficiency across 30 provinces in the Chinese mainland, utilizing panel data from 2011 to 2020. Additionally, this investigation delves into the intervening role of industrial structure upgrading and the amplifying effects of environmental regulation and human capital on the process. Findings indicate that, to begin with, digital infrastructure contributes to the meaningful enhancement of green innovation efficiency within provinces. Subsequently, the industrial structure upgrading partially mediates the impact of digital infrastructure on the efficiency of provincial green innovation. Lastly, both human capital and environmental regulations amplify the beneficial influence of digital infrastructure on the effectiveness of green innovation at the provincial level. This study provides valuable insights into the mechanisms through which digital infrastructure boosts green innovation efficiency, aiding policymakers in formulating appropriate policies to augment digital infrastructure, thereby promoting provincial green innovation efficiency.

Human capital development and economic sustainability linkage in Sub-Saharan African countries: Novel evidence from augmented mean group approach.

Sustainable Development Goal number four (SDG-4) strongly emphasizes quality education, which is crucial to human capital development. The importance of human capital development for sustainable economic development has thus risen to the top of the global policy agenda. However, the empirical literature on the topic has several limitations, including utilizing inappropriate measurement of human capital development and being unable to investigate the quality dimensions of education. Therefore, this study used years of schooling and return on education to fill the gap, and also considered the role of institutional and political factors in its empirical estimation. The main objective of this study is to investigate the effect of human capital development on economic sustainability in 30 Sub-Saharan African countries, employing panel data from 2000 to 2020. The augmented mean group model was used in the empirical investigation. The findings of the study showed that human capital development negatively and significantly affects economic sustainability in Sub-Saharan African countries. Thus, among the policy alternatives that Sub-Saharan African countries and policymakers should pursue to attain the goals of economic sustainability is revisiting the entire human capital development architecture and putting more of an emphasis on quality education than on access to education.