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Background: Air pollution is one of the biggest problems in societies today. The intensity of indoor and outdoor air pollutants and the urbanization rate can cause or trigger many different diseases, especially lung cancer. In this context, this study's aim is to reveal the effects of the indoor and outdoor air pollutants, and urbanization rate on the lung cancer cases. Methods: Panel data analysis method is applied in this study. The research includes the period between 1990 and 2019 as a time series and the data type of the variables is annual. The dependent variable in the research model is lung cancer cases per 100,000 people. The independent variables are the level of outdoor air pollution, air pollution level indoor environment and urbanization rate of countries. Results: In the modeling developed for the developed country group, it is seen that the variable with the highest level of effect on lung cancer is the outdoor air pollution level. Conclusions: In parallel with the development of countries, it has been determined that the increase in industrial production wastes, in other words, worsening the air quality, may potentially cause an increase in lung cancer cases. Indoor air quality is also essential for human health; negative changes in this variable may negatively impact individuals' health, especially lung cancer.

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Health service need refers to the essential care required to achieve optimal health outcomes within resource constraints. When necessary services to address identified health issues are not received, unmet needs arise. This research focuses on the determinants of unmet healthcare needs across the 34 countries within the European region from 2011 to 2019, focusing on Andersen's Behavioral Model's enabling factors. We employed a static and robust panel regression model using Stata 14.0 software. Key determinants analyzed include GDP per capita, urbanization rate, and physicians per capita. Findings reveal that lower GDP per capita and lower urbanization rates are significantly correlated with higher levels of unmet healthcare needs, highlighting income level and geographical accessibility as critical factors. Additionally, a higher number of physicians per capita is associated with reduced unmet healthcare needs, indicating the importance of healthcare resources in addressing healthcare access gaps. These findings underscore the importance of targeted healthcare policies that address income level, improve healthcare accessibility, and enhance healthcare resource allocation to reduce unmet healthcare needs effectively. These findings equip policymakers and administrators with empirically grounded insights to comprehend the factors contributing to unmet healthcare needs and to develop policies aimed at addressing this challenge.

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This study explores the applicability of the Environmental Kuznets Curve (EKC) hypothesis in the United States (US) from 2006 to 2020, employing the Spatial Durbin Model (SDM) to analyze the cross-border effects of pollution among states. The results indicate that although economic growth initially decreases environmental degradation, it subsequently contributes to more significant environmental degradation, challenging the EKC hypothesis's validity at the US state level. Factors such as higher energy prices and reliance on fossil fuels are also identified as significant drivers of environmental deterioration, with varying impacts observed across states. Conversely, adopting renewable energy sources is crucial in mitigating pollution levels. The study underscores the importance of coordinated state-level efforts to harmonize economic growth with sustainable environmental practices. It highlights the complexities of policymaking in balancing economic development with environmental conservation and emphasizes the need for targeted interventions to address environmental challenges effectively. This research enhances our understanding of sustainable development pathways amidst diverse regional dynamics within the US by providing empirical evidence and policy insights.

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B-Corp certification is a fairly modern business phenomenon. Consequently, research on its relationship with key business strategy variables is still inconclusive, while longitudinal analyses of its link to financial performance are scarce. To determine whether business profit could be a robust argument to attract companies to assess and certify their social and environmental impact, in this research we explore the connection that exists between the B-Corp certification and corporate financial performance in the short-, medium- and long-term. For this purpose, we use an international sample of 103 B-Corp companies that have been certified in 2013-2020 and we use the S&P Capital IQ database to collect their economic data. A control sample of non-B-Corp companies is also collected to establish a comparison and avoid bias in the research. The findings show no differences in the performance of B-Corps and non-certified companies before the certification, so a selection effect does not seem to exist in B-Corp certification. Regarding the performance of companies after the certification, known as treatment effect, B-Corps have smaller economic return than pre- and non-certified companies during two years after certification. Nonetheless, after that and in the long run, differences in financial performance between pre-certified and B-Corps are not statistically significant. These findings set the basis for future studies aiming to understand the reasons behind the initial loss of profitability after the B-Corp certification.

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This study employs a comprehensive database of Spanish homes and econometric modeling to assess the factors influencing electricity consumption in Spain. Using panel data covering the period from 1998 to 2023, we analyzed the average yearly electricity usage across the 18 Spanish regions. Our findings reveal that fluctuations in electricity prices have remained the primary driver of consumption over this period. The price elasticity of demand has been exceptionally high, exceeding levels observed in earlier research and periods. Additionally, factors such as income, hours of sunlight, and temperature fluctuations positively influence electricity usage, albeit to a lesser extent than household and family characteristics (e.g., whether a single parent heads the household or if it includes foreign residents). There is no significant correlation between demand and factors such as the age or employment status of family members. Based on these findings, policy actions that target power pricing (e.g., price-based instruments) are likely to be the most effective in reducing electricity consumption.

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A thriving literature exists about the role of financial inclusion in socio-economic development. Nevertheless, the environmental effects of financial inclusion are largely unknown in the literature, especially in sub-Saharan African countries. Therefore, this study explores the association between financial inclusion and CO2 emissions utilizing data from 23 sub-Saharan Africa for the period 2004-2019. Based on different estimation methods such as dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS), canonical correlation regression (CCR), and an instrumental variable generalized-method of moment (IV-GMM), the results show that financial inclusion is responsible for a substantial increase in CO2 emissions. In addition, financial inclusion moderates economic growth, resulting in higher CO2 emissions. Alternatively, financial inclusion moderates renewable energy use to lower CO2 emissions. The outcomes also verify the presence of the Environmental Kuznets Curve hypothesis (EKC). This study proposes uniting financial inclusion and environmental policies as a strategy for reducing CO2 emissions in sub-Saharan Africa.

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BACKGROUND: Ensuring that the scale and hierarchical structure of health human resources are rational, and that medical services are efficient and fair, is an important task of practical significance. On this basis, examining the impact of health human resources on the level of medical services presents a new and formidable challenge. This study aims to delve into how the scale and hierarchical structure of health human resources in China's four major economic regions affect the fairness and efficiency of medical services, and to identify optimization strategies. METHODS: This study utilizes provincial panel data from China's four major economic regions spanning the years 2009 to 2021. Initially, it provides a statistical description of the current state of health human resources and the level of medical services. Subsequently, it employs a fixed-effects model to analyze the impact of the scale and hierarchical structure of health human resources, as well as their interactive effects, on the fairness and efficiency of medical services, and discusses the interactive mechanisms between medical service fairness and medical service efficiency. Furthermore, after conducting a comprehensive evaluation of the level of medical services using the entropy weight method, it explores the regional heterogeneity and temporal dynamics in the influence of the scale and hierarchical structure of health human resources on the level of medical services. Finally, the study examines the scientific validity and rationality of the research findings through various robustness checks, including the substitution of research variables and models. RESULTS: The study found that the scale of health human resources has a promoting effect on the equity of medical services (ß ≤ 0.643, p ≤ 0.01), but exhibits an inhibitory effect on the efficiency of medical services (ß ≥ -0.079, p ≤ 0.1); the hierarchical structure of health human resources shows a positive impact on both the equity and efficiency of medical services (ßequity ≤ 0.160, p ≤ 0.01; ßefficiency ≤ 0.341, p ≤ 0.05); at the same time, the results indicate that the interactive effect of the scale and hierarchical structure of health human resources promotes equity in medical services (ß = 0.067, p ≤ 0.01), but restricts the efficiency of medical services (ß ≥ -0.039, p ≤ 0.01); the mechanism by which health human resources affect the level of medical services in China's western and northeastern regions is more pronounced than in the central and eastern regions; after the implementation of the "Healthy China 2030" Planning Outline, the role of health human resources in the level of medical services has been strengthened; in the robustness tests, the model remains robust after replacing the core explanatory variables, with R2 maintained between 0.869 and 0.972, and the dynamic GMM model test shows a significant second-order lag in the level of medical services (ßequity ≤ 0.149, p ≤ 0.01; ßefficiency ≤ 0.461, p ≤ 0.01); the channel test results prove that managerial personnel and other technical personnel are key pathways in regulating the impact of medical staff on the level of medical services. CONCLUSION: This study provides an in-depth analysis of the impact of health human resources on the level of medical services, revealing that both the scale and hierarchical structure of health human resources significantly affect the equity and efficiency of medical services. Furthermore, the influence of health human resources on the level of medical services exhibits regional heterogeneity and temporal characteristics. Robustness tests ensure the scientific validity and robustness of the research conclusions. This provides effective references for optimizing the allocation of health human resources and improving the level of medical services.

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Introduction: This study investigates the Health-Led Growth Hypothesis (HLGH) within OECD countries, examining how health expenditures influence economic growth and the role of different health financing systems in this relationship. Methods: Utilizing a comprehensive analysis spanning 2000 to 2019 across 38 OECD countries, advanced econometric methodologies were employed. Both second-generation panel data estimators (Dynamic CCEMG, CS-ARDL, AMG) and first-generation models (Panel ARDL with PMG, FMOLS, DOLS) were utilized to test the hypothesis. Results: The findings confirm the positive impact of health expenditures on economic growth, supporting the HLGH. Significant disparities were observed in the ability of health expenditures to stimulate economic growth across different health financing systems, including the Bismarck, Beveridge, Private Health Insurance, and System in Transition models. Discussion: This study enriches the ongoing academic dialog by providing an exhaustive analysis of the relationship between health expenditures and economic growth. It offers valuable insights for policymakers on how to optimize health investments to enhance economic development, considering the varying effects of different health financing frameworks.

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Land-use modeling stands as a pivotal tool in shaping sustainable development policies. With the rapid advancement of remote-sensing technology and the widespread adoption of satellite imagery-based land cover products, these datasets have emerged as primary sources for understanding land-use dynamics due to their high spatial and temporal resolutions. Yet, it remains challenging to effectively integrate such rich panel data into nonlinear econometric land-use models. This paper introduces a method to seamlessly incorporate land cover panel data into econometric models, enabling comprehensive utilization of temporal information within a single framework.-By capturing dynamic land-use patterns, the method enhances prediction accuracy while mitigating issues such as autocorrelated error terms commonly encountered in panel data analysis.-The method is straightforward to implement and applicable to many nonlinear models, making it particularly suitable for datasets with large sample sizes.

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This comprehensive study addresses the urgent global challenges of climate change and environmental degradation by focusing on the Ecological Footprint (EF). Unlike previous studies, it introduces a novel approach incorporating spatial spillover, temporal effects, and common shocks in panel data analysis. The spatial spillover effect highlights the influence of trade, pollution havens, and competition between neighboring countries on EF. The temporal effects emphasize the significance of historical production patterns and export strategies in shaping the current EF. The study also considers the impact of exogenous common shocks, such as international agreements and global events, on EF. Utilizing a dynamic spatial panel data model with common shocks, the research examines 40 European countries from 1992 to 2020, revealing the significant impact of biocapacity, energy consumption, industrialization, and globalization on EF. Findings indicate that spatial spillover effects contribute to EF transfer, emphasizing the need for collaborative global efforts. The study sheds light on the interconnectedness of environmental impacts and underscores the importance of considering both weak and strong forms of cross-sectional dependence in achieving accurate estimations. The research enriches our understanding of EF determinants and provides nuanced insights for policymakers striving to develop effective strategies for sustainable resource management and environmental conservation.

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The global rise of right-wing populist [RWP] parties presents a major political concern. RWP parties' voters tend to be citizens who have either experienced or fear economic deprivation. Income change constitutes a viable measure of this deprivation. However, previous contributions examining effects of income change on support for RWP parties have yielded diverging conclusions. This paper challenges previous findings by incorporating considerations of gender and within-household inequality. We hypothesise a negative relationship between, on the one hand, personal and household income change and, on the other hand, sympathy towards RWP parties. Furthermore, we expect to find a stronger association between personal income change and RWP sympathy among men. Moreover, we expect the relationship between household income change and RWP sympathy to differ between genders. Finally, we hypothesise that this gender disparity can be interpreted by considering who contributes most to the household income. All these hypotheses are grounded in gender socialisation and economic dominance theories. Analysing Dutch LISS longitudinal data spanning from 2007 to 2021 (N = 7,801, n = 43,954) through fixed-effects multilevel linear regression models enables us to address various competing explanations. It appears that only for men, personal income change is negatively linked with sympathies towards RWP parties. However, considering who is the highest earner within households reveals that women are also affected by their personal income change if they earn the highest income. For both men and women, household income change is negatively linked with sympathies towards RWP parties. These results lend partial support to both the socialisation and economic dominance theories. The implications of these findings are discussed.

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Global economic integration and environmental issues have attracted widespread attention in recent years. As one of the world's most significant free trade agreements, the Regional Comprehensive Economic Partnership (RCEP) significantly impacts trade and the environment. However, research on the relationship between trade costs and carbon emissions still needs to be completed. This study explores the relationship between trade costs and carbon emissions within the framework of the Trade Benefit Theory, which posits that trade liberalization and openness generate economic benefits through increased efficiency, technological advancement, and economic growth. This study analyzes panel data from 12 RCEP countries from 2001 to 2014, employing static and dynamic panel models to examine the relationship between trade costs and carbon emissions. The analysis utilizes mixed regression, fixed (random) effects models, and the systematic GMM method. The results indicate that decreases in trade costs are associated with reduced environmental pollution, aligning with the Environmental Kuznets Curve (EKC) hypothesis, which posits an N-shaped relationship between trade costs and carbon emissions. Implementing RCEP facilitates a decrease in trade-related pollution, suggesting that reducing trade costs can help mitigate environmental pollution. Furthermore, the observed N-shaped EKC for trade costs and carbon emissions highlights the potential of RCEP to reduce the impact of trade-related pollution.

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BACKGROUND: This study updates our findings from the COVID-19 pandemic surveillance we first conducted in South Asia in 2020 with 2 additional years of data for the region. We assess whether COVID-19 had transitioned from pandemic to endemic at the point the World Health Organization (WHO) ended the public health emergency status for COVID-19 on May 5, 2023. OBJECTIVE: First, we aim to measure whether there was an expansion or contraction in the pandemic in South Asia around the WHO declaration. Second, we use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history. Third, we aim to provide historical context for the course of the pandemic in South Asia. METHODS: In addition to updating the traditional surveillance data and dynamic panel estimates from our original study, this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a 1-sided t test to determine whether regional weekly speed or transmission rate per 100,000 population was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data across the sample period. RESULTS: Speed for the region had remained below the outbreak threshold for over a year by the time of the WHO declaration. Acceleration and jerk were also low and stable. While the 1-day persistence coefficients remained statistically significant and positive (1.168), the 7-day persistence coefficient was negative (-0.185), suggesting limited cluster effects in which cases on a given day predict cases 7 days forward. Furthermore, the shift parameters for either of the 2 most recent weeks around May 5, 2023, did not indicate any overall change in the persistence measure around the time of the WHO declaration. From December of 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t test of speed equal to 10 was statistically insignificant across the entire pandemic. CONCLUSIONS: While COVID-19 continued to circulate in South Asia, the rate of transmission had remained below the outbreak threshold for well over a year ahead of the WHO declaration. COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. Both standard and enhanced surveillance metrics confirm that the pandemic had ended by the time of the WHO declaration. Prevention policies should be a focus ahead of future pandemics. On that point, policy should emphasize an epidemiological task force with widespread testing and a contact-tracing system.

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As the main vehicle for the tertiary distribution, charity has a certain regulating effect on regional medical level. However, the improvement of regional medical effect of charity has yet to be tested. Based on provincial panel data from 1997 to 2019, this study analyzes the impact of charitable donations on regional medical level. The empirical results show that charitable donations widen the gap of overall regional medical level in China, which not only results from the current period but also from charity accumulation in the past. The regional heterogeneity analysis show that charitable donations have expanded the regional medical level of the eastern and western regions, while have no significant effect on the regional medical level gap in the central region. The widening effect in the eastern region of charitable donations is the largest. In addition, charitable donations expand the regional medical level gap between urban and rural areas in China. Charity, as the regional medical development mechanism, has not yet played its due role and advantages in regulating regional medical level gap. Formulating and adjusting the corresponding charity promotion policies is necessary.

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This study reexamines the causal nexus among electricity consumption (EC) and economic growth (EG) for a panel of 31 countries in Latin America and the Caribbean between 1980 and 2021. We find that there are statistically significant feedback impacts among the research variables in the long run. A 1 percent augment in EC raises EG by 0.5 percent and a 1 percent augment in EG produces a 1.54 percent increase in EC which reflects the nature of the latter as a luxury good and implies a tradeoff between economy and environment, since although greater electrical infrastructure drives EG, the latter also increases the EC whose use in a non-responsible manner could lead to environmental degradation through higher CO2 emissions. Therefore, the main policy implication is that, it is necessary to promote EG based on infrastructure focused on sustainable development, ensuring the well-being of present and future generations.

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The purpose of this study is to examine the impact of national savings on economic development, as measured by the Human Development Index (HDI), Inequality-adjusted HDI (iHDI), and Multidimensional Poverty Index (MPI), in ten of the poorest countries in Sub-Saharan Africa. The study employs a sequential Generalized Method of Moments (GMM) analysis to address potential endogeneity issues and account for the dynamic nature of the relationships, covering the period from 2009 to 2019. The findings reveal a complex relationship between national savings and the selected development indicators. While national savings exhibit positive impacts on HDI and iHDI, the results are not consistently statistically significant across all the sequential models. However, the analysis suggests that national savings have a positive influence on reducing multidimensional poverty, as measured by MPI, particularly when effectively channeled into productive investments. The study also highlights the significant positive impact of government expenditure and foreign direct investment (FDI) on human development, underscoring the importance of strategic public investments and foreign capital. The results suggest that while national savings are crucial, their effective utilization is essential for enhancing human development indices. Strategic investments in public goods and foreign capital are also important. The mixed effects of inflation and official development assistance (ODA) emphasize the need for stable economic policies and effective utilization of foreign aid. The modest positive impact of institutional quality suggests that improvements in governance and institutional frameworks can contribute to human development. The findings underscore the need for policies promoting financial inclusion, efficient public expenditure, foreign direct investment, and stable macroeconomic conditions to leverage national savings for economic development. The study's findings provide valuable insights for policymakers in Sub-Saharan Africa, highlighting the need for comprehensive strategies that leverage national savings, public expenditure, and foreign investment to drive sustainable economic development and poverty reduction.

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The following article presents an analysis of the impact of the Environmental, Social and Governance-ESG determinants on Hospital Emigration to Another Region-HEAR in the Italian regions in the period 2004-2021. The data are analysed using Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled Ordinary Least Squares-OLS, Weighted Least Squares-WLS, and Dynamic Panel at 1 Stage. Furthermore, to control endogeneity we also created instrumental variable models for each component of the ESG model. Results show that HEAR is negatively associated to the E, S and G component within the ESG model. The data were subjected to clustering with a k-Means algorithm optimized with the Silhouette coefficient. The optimal clustering with k=2 is compared to the sub-optimal cluster with k=3. The results suggest a negative relationship between the resident population and hospital emigration at regional level. Finally, a prediction is proposed with machine learning algorithms classified based on statistical performance. The results show that the Artificial Neural Network-ANN algorithm is the best predictor. The ANN predictions are critically analyzed in light of health economic policy directions.

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This paper considers estimating functional-coefficient models in panel quantile regression with individual effects, allowing the cross-sectional and temporal dependence for large panel observations. A latent group structure is imposed on the heterogenous quantile regression models so that the number of nonparametric functional coefficients to be estimated can be reduced considerably. With the preliminary local linear quantile estimates of the subject-specific functional coefficients, a classic agglomerative clustering algorithm is used to estimate the unknown group structure and an easy-to-implement ratio criterion is proposed to determine the group number. The estimated group number and structure are shown to be consistent. Furthermore, a post-grouping local linear smoothing method is introduced to estimate the group-specific functional coefficients, and the relevant asymptotic normal distribution theory is derived with a normalisation rate comparable to that in the literature. The developed methodologies and theory are verified through a simulation study and showcased with an application to house price data from UK local authority districts, which reveals different homogeneity structures at different quantile levels.

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This study examines the impact of India's export restrictions on domestic retail rice prices using a dynamic panel GARCH model. The findings suggest that export restrictions are not a sufficient condition to lower domestic prices. Export restrictions are associated with lower retail price volatility in the East Zone. Moreover, the international price transmission to a sample of Asian and African economies shows that all countries are vulnerable, but the degree and kinds of vulnerability differ. Rice exporters appear to be the most susceptible as domestic prices increase in these countries. Rice importers are also vulnerable because of price increases, but the increases are less than in countries where the private sector decides on import quantities.

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This study employs Fully Modified Ordinary Least Squares, Common Correlated Effects and Dumitrescu-Hurlin panel causality techniques to investigate the environmental impacts of nuclear energy generation in European Union countries from 1990 to 2022. The ongoing debate within the European Union and the empirical contradictions in the literature, coupled with the overall singular-dimensionality surrounding the impacts of nuclear energy on the environment, necessitate a broader and comprehensive examination of its effects across various environmental dimensions. These dimensions include the presence of CO2 emissions and the ecological footprint generated. The findings reveal that nuclear energy adoption by countries tends to affect CO2 emissions but this relationship goes from CO2 to nuclear energy consumption as per the causality test, while the ecological footprint variable does not exhibit a causal relationship with nuclear energy consumption. We estimated that a higher presence of air pollutants promotes the generation of nuclear energy as an alternative to fossil fuel energy sources. The study highlights that while nuclear energy generation produces no air pollution, it does impose significant land use requirements, potentially leading to ecosystem degradation. Factors such as uranium extraction, nuclear waste management, disposal, and accidents contribute to this impact. Further research is needed to understand the specific mechanisms and factors contributing to the observed environmental degradation associated with nuclear energy generation.