Search Results (631)

The role of renewable energy (REN) in promoting economic growth and improving environmental quality has been widely debated and extensively researched in the existing body of knowledge during the last couple of decades. However, the specific role of REN in promoting sustainable development (SUD) is yet to be researched in the presence of the moderating role of institutional quality in the context of G-7 economies. Accordingly, this research study attempts to explore the potential relationship between REN and SUD in the presence of the moderating role of institutional quality by utilizing data from G-7 economies for the period 2002–2022. Acknowledging the presence of cross-sectional dependency, serial correlation, and heteroscedasticity, the present study used the fixed effects estimator with Driscoll–Kraay standard errors. The results demonstrated a positive and statistically significant influence of REN on SUD. Furthermore, the findings demonstrated that institutional quality moderates the relationship between REN and SUD and sustainable development effectively. Moreover, we found that trade openness and unemployment rate are the main driving forces of SUD. In addition, we found that government expenditures, inflation rate, and CO₂ emissions are detrimental from the perspective of SUD. Finally, we found that industrialization and institutional quality in isolation are unable to explain variation in the level of SUD in the case of G-7 economies. The causality analysis also demonstrated a one-way causal impact of REN on SUD. The study’s findings offer valuable policy suggestions related to the transition towards REN and accelerating the pace of SUD for the consideration of the policymakers of G-7 economies. Full article

Statistical Process Control (SPC) plays a crucial role in monitoring and improving manufacturing processes to ensure product quality. Control charts using exponentially weighted moving averages (EWMA) and their extensions, including Extended EWMA (EEWMA) and New Extended EWMA (NEEWMA), have been developed to increase the sensitivity for detecting small to medium process changes. This research proposes a method for calculating the Average Run Length (ARL) and Standard Deviation of Run Length (SDRL) of control charts under a symmetric distribution using the Markov Chain Approach (MCA). This method is based on the probability of state transitions between controlled and uncontrolled states. The MCA method is more efficient than the Monte Carlo Simulation Approach (MC) in terms of accuracy and significantly reduces processing time. This research also demonstrates the application of ARL and SDRL calculations using the MCA method in various studies. Firstly, the performance of control charts is compared using the Mean Percentage Error (MPE) and Mean Absolute Percentage Error (MAPE). Secondly, the impact of symmetrically distributed process parameters on the performance of control charts is examined. Thirdly, a practical application of the control charts is presented. This research applies the proposed method to detect changes in unemployment insurance claims (UI) using seasonally adjusted initial claims assessment (ICSA) and continuing claims assessment (CCSA) rates from 2021 to 2025. The results show that the MCA method is more efficient than the MC method in terms of accuracy and significantly reduces processing time. Full article

Background/Objectives: Health system socio-economic inequities in dental care are a long-standing problem in Europe. The issue gained increased relevance during the recent pandemic due to service disruption and socio-economic inequities that become even more pronounced under such circumstances. However, while preventive dental programs are considered key elements of public health, little is known about their role in addressing equity in accessing dental care among different countries and over time between them. This research aims at investigating the relationship between preventive dental policy, socio-economic factors, and the inability to get appropriate dental care within EU member states. Methods: A longitudinal panel dataset at the country level, consisting of data collected during 2020 through 2024, was assembled using open sources of statistics from Europe and other international statistical databases. The dependent variable used in the study was the percentage of the population that had unmet dental care need because of cost. Independent variables were the presence or absence of preventive policies related to dentistry, educational attainment, gross domestic product per capita, unemployment rate, number of dentists, and out-of-pocket expenses. Balanced panel datasets and regressions with robust standard errors in random-effects models were estimated. Interaction terms were created to test the moderating effect of education level on the relationship between policies and access to care. Results: Cross-country variations in terms of the prevention policy environment, socio-economic status, and unmet dental care need were found from descriptive analysis. The higher level of out-of-pocket payment was always related to the higher unmet dental care need, while the lower GDP countries displayed poorer access. Using the balanced panel random-effects model, preventive dental policies and the interaction between preventive policies and educational level were insignificant factors predicting the unmet dental care need. On the other hand, higher out-of-pocket payments, education, and dentists per million population had nearly significant positive relationships. In the sensitivity analysis, GDP per capita showed a negative association, whereas dentists per million population remained positively associated with unmet dental care need. Conclusions: The findings suggest that inequalities in access to dental care during and after the COVID-19 period were shaped primarily by financial and structural determinants rather than by the presence of preventive policies alone. While preventive programs remain an important component of long-term oral health strategies, reducing direct household payment burden and strengthening health system capacity may represent more immediate mechanisms for maintaining equitable access to dental services during periods of system disruption. Full article

Urban development in medium-sized provinces is increasingly influenced by the interplay of demographic change, socio-economic disparity, and labour market structure. However, these dimensions are frequently examined in isolation, which limits their utility for integrated regional planning. This study offers a planning-oriented assessment of Amasya Province, Türkiye, by integrating population projections, district-level socio-economic disparity analysis, and labour market indicators to evaluate the province’s developmental trajectory toward 2035. The study utilizes official population data for 2007–2024, district-level socio-economic status scores for 2023, and provincial labour market indicators. Linear trend projection and compound annual growth rate analysis were employed to estimate population change, while the Gini coefficient, Theil index, and coefficient of variation were used to assess intra-provincial socio-economic disparities. Labour market performance was evaluated through participation, employment, unemployment, and employment-to-participation efficiency indicators. The results indicate that Amasya is projected to experience a moderate population increase, reaching approximately 350,118 inhabitants by 2035. Growth is anticipated to remain concentrated primarily in the Central District and Merzifon, while socio-economic advantages also exhibit a central–peripheral pattern. Labour market indicators suggest relatively stable employment performance, although more detailed sectoral, gender, and age-specific analyses are necessary for more robust conclusions. The study contributes an integrated framework for linking demographic projection, socio-economic hierarchy, and labour market capacity in medium-sized provincial planning. The findings suggest that future planning should focus on managing growth in central districts while supporting balanced development in peripheral districts. Full article

Purpose: Purchased/Referred Care Delivery Area (PRCDA) counties are those where resident American Indian and Alaska Native (AIAN) people are eligible for Indian Health Service care. Due to concerns about racial misclassification, cancer statistics for AIAN people are often restricted to PRCDA counties. Differences in sociodemographic characteristics may exist between PRCDA and non-PRCDA counties, but have not been described; therefore, the potential selection bias associated with the restriction to PRCDA counties remains unknown. Methods: We used data from the University of California, San Francisco Health Atlas to explore ecological differences in county-level demographic, socioeconomic, healthcare access, and health outcomes data between PRCDA and non-PRCDA counties (n = 3152 counties). We tested for statistical differences in mean levels of demographics between PRCDA and non-PRCDA counties using Pooled or Welch t-tests. Results: We observed small, but statistically significant differences between PRCDA and non-PRCDA counties in county-level demographic and socioeconomic characteristics (age, poverty, utility services threat, unemployment, educational attainment, computer access, and median income), neighborhood and environment characteristics (overcrowding, severe mortgage/rent burden), healthcare access and utilization (uninsured, annual checkup, annual dental visit, mammography, binge drinking, smoking, physical inactivity, social isolation), and health outcomes (poor mental health, arthritis, poor self-rated health, high blood pressure, diabetes, high cholesterol, and obesity). Conclusions: These results indicate variability in county-level measures between PRCDA and non-PRCDA counties. While these data do not speak specifically to AIAN peoples’ experiences, they provide critical contextual information to understand how exclusion of AIAN people residing in non-PRCDA counties from cancer statistics may bias risk estimates. Full article

This article examines two-state proportional hazard rate models with unobserved heterogeneity specific to each state, a framework that is especially relevant for labor market transitions. To make estimation feasible in large longitudinal datasets, we implement hshaz2s, a Stata routine that uses analytical expressions for the gradient vector and Hessian matrix of the log-likelihood function through the dual second-order moment (d2 ml) method. The empirical application estimates a discrete-time duration model for transitions between employment and unemployment using Spanish labor market microdata for young low-skilled workers over 2000–2019. The results show that apprenticeship contracts are associated with lower exit rates from employment than other temporary contracts, but not with faster transitions from unemployment back into employment. The estimates also reveal substantial state-specific unobserved heterogeneity, with a large latent group characterized by persistent spells in both states. Analytical second-order information also markedly reduces convergence time under richer heterogeneity structures. Overall, the article makes this class of two-state hazard models operational for applied research and provides new evidence on apprenticeship and temporary contracts in Spain. Full article

In the current labor market, perceived employability is a key resource for university students approaching the transition from university to work, which is often marked by heightened stress, vulnerability, and unhealthy behaviors, particularly in contexts with high youth unemployment rates. Despite prior research documenting the buffering role of perceived employability in the relationships between career-related stressors and well-being, limited evidence exists regarding the roles of faculty support and self-compassion, a fundamental factor for effective emotional regulation, during university years. Consequently, this study aimed to examine the relationships between faculty support, self-compassion, career self-efficacy, career planning, and perceived employability through a self-report questionnaire completed by 186 Italian university students, mainly female, with a mean age of 21.24 (SD = 2.57). Results from a partial least squares model indicated that faculty support was indirectly associated with perceived employability through self-compassion, career self-efficacy, and career planning. These findings could support higher education organizations by suggesting the design of interventions to promote supportive learning environments and to develop training in emotional regulation skills. Such an approach could empower students to effectively cope with career-related stressors and, in turn, engage in adaptive behaviors associated with employability. Full article

The Disability Royal Commission in Australia has reinforced concerns that segregated employment settings can increase risks of exploitation, violence and abuse, including within Australian Disability Enterprises (ADEs), strengthening the case for community-based employment options for people with intellectual disability. This qualitative study examined how features of supported employment might inform the design of an inclusive job guarantee (JG) model. Drawing on 77 interviews with supported employees and staff, we identified enabling conditions that support wellbeing and participation (including customised roles, structured routines, peer connection, and holistic support), alongside structural constraints that can limit inclusion and progression. While participants and staff described clear well-being benefits from supported employment, they also highlighted frustrations associated with disconnection from the wider community, low pay, and limited pathways to advancement or transition. Given that transition rates between supported and mainstream employment remain very low, the findings emphasise that any JG model seeking to include people with intellectual disability will need investment in supports and credible transition pathways. This paper concludes by outlining how these design implications intersect with the broader economic logic of unemployment and what an inclusive JG could contribute as part of a wider disability employment reform agenda. Full article

This paper provides a comparative analysis of the economic crises in Argentina and Lebanon to derive policy-relevant lessons for the design of IMF-supported adjustment programs in fragile economies. Using a structured comparative case study approach, the study examines crisis dynamics, policy responses, and socioeconomic outcomes across both countries, with particular attention given to exchange rate collapse, banking sector distress, public debt, inflation, unemployment, and poverty. The findings suggest that programs centered primarily on macroeconomic stabilization and fiscal austerity, without adequate attention to institutional capacity, social protection, and debt restructuring, risk deepening economic contraction and social vulnerability. The Argentine experience shows that IMF-supported adjustment in institutionally fragile environments may fail to restore confidence or deliver sustainable recovery when reform sequencing is weak and complementary domestic policies are absent. For Lebanon, where the crisis is deeper and compounded by governance failures and geopolitical instability, IMF engagement appears necessary but insufficient on its own. The paper concludes that a sustainable recovery requires a hybrid strategy combining external financial support with country-specific reforms, including exchange rate unification, banking sector restructuring, debt resolution, stronger governance, and targeted social protection. Full article

Radon (²²²Rn₈₆), the second leading cause of lung cancer, is common in indoor air. However, radon testing is generally low throughout the US. In this study, we utilized 134,496 short-term indoor air radon test results from Georgia, USA. We investigated the association of the radon testing rate with a total of 104 different independent variables belonging to seven categories: (1) Demographic and Neighborhood Characteristics; (2) Housing Characteristics; (3) Literacy and Numeracy; (4) Employment and Economy; (5) Selected Social Factors; (6) Access to Computer/Internet; and (7) Status of Healthcare, Health, Well-being, and Lifestyle. We used Bivariate Correlation, Multivariate Ordinary Least Squares (OLS) Regression, and Factor Analysis, followed by factor score-based OLS regression. Significant negative associations of the testing rates were observed with population diversity, residential segregation, urban population density, younger population, housing age, household size, low literacy, unemployment, childcare cost burden, poverty, obesity, and the frequency of mentally and physically unhealthy days. In contrast, testing rates were positively associated with older population, home value, owner-occupied homes, higher literacy, higher institutional education, income, prevalence of social association, and life expectancy. The findings provide valuable insights for identifying the communities where socio-culturally relevant outreach activities would increase testing rates and minimize the public health consequences of environmental radon. Full article

Background/Objectives: The implementation of COVID-19 vaccination in the United States has revealed substantial disparities driven by geography, socioeconomic conditions, and political ideology. This study examines the association between these factors and COVID-19 vaccination uptake across 360 counties in four U.S.–Mexico border states, characterized by distinct socio-political traits. Methods: Using county-level data, this study employed multivariable regression analysis and GIS mapping to assess the effects of income, education, employment, age, race, ethnicity, occupation, metropolitan status, border status, and political affiliation on Dose 1, Dose 2, and booster vaccination rates. Results: The analysis showed that Dose 1 vaccination rates were significantly higher in border counties and metropolitan areas. Democratic population share and per capita income were positively associated with vaccination uptake. Dose 2 vaccination rates exhibited patterns similar to those observed for Dose 1. Booster vaccination rates were positively associated with Democratic affiliation, the proportion of the population with at least a high school education, and the share of individuals aged 65 years and older. In contrast, unemployment rates were negatively associated with booster uptake. Racial and ethnic composition was also associated with vaccination outcomes: higher Black population shares were associated with lower Dose 1 vaccination rates, whereas higher Native American population shares were associated with higher vaccination rates. Booster uptake was higher with larger shares of the Asian population but slightly lower with larger shares of the White population. Conclusions: COVID-19 vaccination uptake in U.S.–Mexico border counties was associated with a complex interaction of geographic, socioeconomic, demographic, and political factors. These findings underscore the importance of targeted, context-specific public health strategies to reduce vaccination disparities and improve booster coverage in border regions. Full article

It is widely recognised that rural tourism influences the socio-economic structure of rural areas. Less attention, however, has been given to the reverse relationship—namely, how the economic conditions of rural municipalities shape the level and diversity of their tourism functions. This publication represents an effort to enrich research in this area. The study aimed to identify the relationships between selected economic indicators of rural areas and the level of their tourism function. The study’s spatial scope covered 1498 rural municipalities in Poland. The temporal scope encompassed the years 2018–2023, which were divided into three sub-periods: 2018–2019, 2020–2021, and 2022–2023. To achieve the research objective, the following methods were applied: the Zero Unitarisation Method, correlation analysis, and linear mixed-effects models. The constructed synthetic tourism function index enabled distinguishing between rural areas with high and low tourism attractiveness. The analysed rural municipalities exhibited considerable variation in the constructed index. The correlation analysis across four groups of rural areas, classified by the level of the tourism function index and selected economic indicators, revealed only weak to moderate relationships in the group of rural municipalities with a high level of tourism attractiveness (group 1). No such relationships were identified in the remaining groups of rural areas. The mixed-effects model further demonstrated that, among the six analysed economic indicators, the entrepreneurship rate and the unemployment rate had statistically significant effects on the tourism function index value. Group affiliation and the time factor exerted a strong and unambiguous influence on the dependent variable. Full article

This study explores Nigeria’s bioenergy industry’s potential in reducing unemployment. It focuses on two objectives: first, to determine how the development of the bioenergy sector can reduce Nigeria’s unemployment rate, and second, to identify effective policy instruments to harness the potential of the bioenergy industry in Nigeria. Using a Forest and Agricultural Sector Optimization Model for Nigeria, this study modeled three scenarios with varying labor wage rates. The second scenario used an hourly wage of US$0.38/h for US$3.00 purchasing power parity (PPP), reflecting the International Labor Organization’s global minimum PPP. The first and third scenarios applied prices slightly below and well above the PPP at the rate of US$0.32/h for US$2.56 PPP and US$1.04/h for US$8.30 PPP, respectively. This was modeled against the baseline labor rate (Nigeria’s minimum wage of 45 USD/month, approximately US$0.28/h, equivalent to 70,000 NGN). Nigeria’s current energy and food security targets and policies are also implicitly implemented. The product-demand driver is the Nigerian population data projection, which aligns with the Shared Socioeconomic Pathways (SSPs) for Scenario 2. Results reveal that while increases in the labor wage rate improve labor welfare above the global poverty threshold, they also impact the bioenergy sector and the aggregated total economic welfare. Results highlight an optimal wage balance where employment growth in the bioenergy sector can be sustained without compromising production capacity or aggregated total welfare. Based on these insights, actionable policy implications from this study include implementing moderate wage growth, subsidies, and productivity investments to maximize bioenergy’s potential as a sustainable employment generator in Nigeria. Full article

Background: Tuberculosis remains a major global public health challenge. Mathematical models are essential for strategic planning and evaluation of tuberculosis control programs, while addressing socioeconomic risk factors has proven key to accelerating incidence declines. Therefore, this study quantitatively assesses the impact of socioeconomic interventions on tuberculosis incidence in Kazakhstan. Methods: A modified SIR compartmental model was developed in Python 3.12 to simulate tuberculosis transmission dynamics. Parameters were calibrated using the Nelder–Mead simplex algorithm, and predictive performance was evaluated via hold-out validation. Scenario-based projections were generated to explore the impact of socioeconomic improvements on future tuberculosis incidence. Results: The calibrated SIR model demonstrated strong predictive accuracy, achieving a mean absolute percentage error of 2.3%. The sensitivity analysis revealed that the model is robust to moderate socioeconomic perturbations, with healthcare funding and unemployment rate as the primary uncertainty drivers. Scenario simulations showed that enhanced financial assistance for tuberculosis patients produced the largest effect beyond baseline. Optimization results indicate that 7.4% rise in GDP per capita, 10.2% increase in healthcare funding, 23.1% and 19.1% reductions in poverty and unemployment rates, and 40.2% growth in tuberculosis patient financial support relative to 2024 are sufficient to achieve the WHO’s End TB Strategy 2030 target. Conclusions: The model offers a valuable tool for tuberculosis forecasting and intervention evaluation, highlighting the synergistic role of socioeconomic measures in achieving global elimination goals. Full article

Attaining education sustainability is indeed important as it ensures the overall economic sustainability of countries and it is directly connected with the United Nations Sustainable Development Goals (SDG-4). However, the literature evidence on the determinants of education sustainability is indeed very scarce and largely inconclusive, particularly in the case of the Kingdom of Saudi Arabia (KSA). Accordingly, this research paper focuses on exploring the determinants of education sustainability by focusing on the role of government education spending. The paper utilized annual time series data for the period 1991–2023 and applied the time series cointegration technique of “Autoregressive Distributed Lag (ARDL)” to assess the long-run and short-run impact of government education expenditures on education sustainability in KSA Our results based on the ARDL approach demonstrated that government expenditures have casted a positive influence on education sustainability both in the long run and short run in the case of KSA. Similarly, we found that trade openness, which is the main determinant of economic performance, has positively contributed to education sustainability in the long run and short run in KSA. On the other hand, the unemployment rate has worsened education sustainability both in the long and short run. The results further demonstrated a negative short-run impact that FDI has on education sustainability, suggesting structural or sectoral dynamics that need further empirical investigation. Moreover, GDP per capita has improved education sustainably only in the long run while its short-run impact is insignificant. Our results offer important policy implications for the policymakers of KSA to attain education sustainability and contribute to the overall economic sustainability, which is aligned with the Vision 2030 of KSA. Full article