Search Results (561)

The transportation sector is a major consumer of primary energy and is a significant contributor to greenhouse gas emissions. Sustainable transportation requires identifying and quantifying factors influencing transport-related CO₂ emissions. This research aims to establish an adaptable, precise, and transparent forecasting structure for transport CO₂ emissions of the United States. For this reason, we proposed a multi-stage method that incorporates explainable Machine Learning (ML) and Feature Selection (FS), guaranteeing interpretability in comparison to conventional black-box models. Due to high multicollinearity among 24 initial variables, hierarchical feature clustering and multi-step FS were applied, resulting in five key predictors: Total Primary Energy Imports (TPEI), Total Fossil Fuels Consumed (FFT), Annual Vehicle Miles Traveled (AVMT), Air Passengers-Domestic and International (APDI), and Unemployment Rate (UR). Four ML methods—Support Vector Regression, eXtreme Gradient Boosting, ElasticNet, and Multilayer Perceptron—were employed, with ElasticNet outperforming the others with RMSE = 45.53, MAE = 30.6, and MAPE = 0.016. SHAP analysis revealed AVMT, FFT, and APDI as the top contributors to CO₂ emissions. This framework aids policymakers in making informed decisions and setting precise investments. Full article

Unemployment and weak economic productivity are significant global issues, particularly in West Africa. Recently, through diverse mechanisms, remittances and foreign direct investment (FDI) have been sources of foreign capital flow that have positively influenced many less developed economies, including ECOWAS (ECOWAS stands for Economic Community of West African States). Nevertheless, these financial flows have exhibited significant inconsistencies, primarily resulting from economic downturns in migrants’ destination countries, with remarkable implications for beneficiary economies. This study, therefore, examines the effect of remittances and FDI on employment in ECOWAS. Specifically, the study assesses the effects of the inflow of remittances and FDI on employment using panel dynamic ordinary least squares (PDOLS) and also investigates the shock effects of remittances and FDI by employing Panel Vector Error Correction (PVECM), which involves variance decomposition. The results show that foreign direct investment (FDI) positively and significantly affects employment. Other variables that show a significant relationship with employment are wage rate, education expenditure, and interest rate. The variance decomposition result revealed that external shocks on remittances and FDI have short- and long-term effects on employment. The above findings imply that foreign direct investment has a far-reaching positive impact on the economy-wide management of the West African sub-region and thus calls for relevant policy options. Full article

The COVID-19 pandemic triggered unprecedented economic disruptions, raising critical questions about the resilience and adaptability of macroeconomic productivity across countries. This study examines the impact of COVID-19 on macroeconomic efficiency and productivity dynamics in 37 OECD countries using quarterly data from 2018Q1 to 2024Q4. By employing a Slack-Based Measure Data Envelopment Analysis (SBM-DEA) and the Malmquist Productivity Index (MPI), we decompose total factor productivity (TFP) into efficiency change (EC) and technological change (TC) across three periods: pre-pandemic, during-pandemic, and post-pandemic. Our framework incorporates both desirable (GDP) and undesirable outputs (inflation, unemployment, housing price inflation, and interest rate distortions), offering a multidimensional view of macroeconomic efficiency. Results show broad but uneven productivity gains, with technological progress proving more resilient than efficiency during the pandemic. Post-COVID recovery trajectories diverged, reflecting differences in structural adaptability and innovation capacity. Regression analysis reveals that stringent lockdowns in 2020 were associated with lower productivity in 2023–2024, while more adaptive policies in 2021 supported long-term technological gains. These findings highlight the importance of aligning crisis response with forward-looking economic strategies and demonstrate the value of DEA-based methods for evaluating macroeconomic performance beyond GDP. Full article

Background: Non-adherence to anti-tuberculosis treatment remains a major obstacle to increasing tuberculosis treatment success rates and enhancing healthcare expenditure. The aim of this study was to identify determinants contributing to non-adherence to anti-tuberculosis treatment in a public primary healthcare clinic in South Africa. Method: A cross-sectional study was carried out to collect data from 65 participants using face-to-face interviews with a structured questionnaire. Data were analyzed using SPSS. Results: Of the 65 participants interviewed, 41 (63.08%) were males and 24 (36.92%) were females. A total of 45 (69.23%) were adherents and 20 (30.77%) were non-adherents. Gender was the major predictor of non-adherence with more males committed to treatment than females with a significant association (X² = 65.00 and p of <0.001). Conclusions: The major contributing factors to non-adherence were long dis-tances to the clinics, a lack of family support, and unemployment. Comprehensive programs addressing these multifactorial factors are needed for successful treatment and eradication of tuberculosis. Full article

The measurement of national well-being has become central to both academic and policy debates, particularly within the framework of sustainable development. In this context, this study investigates the relationship between macroeconomic conditions and subjective well-being in Portugal. Using annual data from 2004 to 2022, we explore the effects of GDP per capita, unemployment, and inflation on the Global Well-Being Index (GWBI). Employing ordinary least squares (OLS) regression, the results indicate a significant positive relationship between GDP per capita and subjective well-being, while inflation is negatively associated. Contrary to expectations, the unemployment rate showed a positive and significant association with the GWBI. This counterintuitive result may reflect institutional buffering effects, such as social safety nets, strong family structures, or lagged responses in perceptions of well-being. Similar patterns were observed in other southern European countries with strong informal social support systems. These findings contribute to a deeper understanding of how economic indicators relate to perceived well-being, particularly in the context of a southern European country. The study offers relevant insights for public policy, including the alignment of macroeconomic management with the Sustainable Development Goals (SDGs), especially SDG 3 (Good Health and Well-being) and SDG 8 (Decent Work and Economic Growth). Full article

This study aims to map the scientific knowledge of bank profitability and its determinants. It identifies trends and gaps in existing research through a bibliometric analysis. To this end, 634 documents published in the Web of Science database over the last 54 years were analyzed using the bibliometric package. The results indicate an increase in the volume of publications following the 2008 financial crisis, focusing on analyzing the factors influencing bank profitability and economic growth. The Journal of Banking and Finance is the preeminent publication in this field. The literature reviewed shows that bank profitability depends on internal factors (size, credit risk, liquidity, efficiency, and management) and external factors (such as GDP, inflation, interest rates, and unemployment). In addition to the traditional determinants, the recent literature highlights the importance of innovation and technological factors such as digitalization, mobile banking, and electronic payments as relevant to bank profitability. ESG (environmental, social, and governance) and governance indicators, which are still emerging but have been extensively researched in companies, indicate a need for evidence in this area. This paper also provides relevant insights for the formulation of monetary policy and the strategic formulation of banks, helping managers and owners to improve bank performance. It also provides directions for future empirical studies and research collaborations in this field. Full article

This paper analyzes how two major economic downturns—a recession and a stagflation—affected convergence in the European Union (EU). Absolute and conditional convergence rates are estimated using ordinary least squares (OLS) semilog regressions based on cross-sectional data from 2004 to 2022. The study tests two hypotheses: there was no absolute convergence in the EU during either the recession or the stagflation period, and conditional convergence occurred during the recession but not during stagflation. The regression results indicate that neither hypothesis can be rejected. External variables—economic openness, inflation, and investment—were more influential during stable periods, whereas internal variables—debt, unemployment, and the control of corruption—had a greater impact during crises. These findings suggest that the EU was more institutionally prepared for the stagflation due to mechanisms developed after the financial crisis, but these tools proved less effective in addressing supply-side shocks. Full article

Antimicrobial resistance (AMR) represents a critical global health threat, with inappropriate antibiotic self-medication (ASM) being a key contributor. China—as the world’s largest antibiotic consumer—faces significant challenges despite regulatory efforts, compounded by limited contemporary data during the COVID-19 pandemic. A nationwide cross-sectional study was conducted using the 2021 China Family Health Index Survey (n = 11,031 participants across 120 cities). Trained investigators administered face-to-face questionnaires assessing ASM practices, decision-making factors, and sociodemographic characteristics. Multivariate logistic regression identified determinants of ASM. Overall, ASM prevalence was 33.7% (n = 3717), with no urban-rural difference (p > 0.05). Physician advice (78.2%), drug safety (67.1%), and efficacy (64.2%) were primary selection criteria; rural residents prioritized drug price and salesperson recommendations more than their urban counterparts (p < 0.01). Key predictors included higher ASM odds among females (OR = 1.30, 95%CI:1.18–1.43), middle-aged adults (46–59 years; OR = 1.20, 95%CI:1.02–1.42), those with health insurance (resident: OR = 1.33; commercial: OR = 1.62), and individuals with drinking histories (OR = 1.20, 95%CI:1.10–1.31). Lower odds were associated with primary education (OR = 0.69, 95%CI:0.58–0.81), unemployment (OR = 0.88, 95%CI:0.79–0.98), and absence of chronic diseases (OR = 0.56, 95%CI:0.47–0.67). One-third of Chinese residents engaged in ASM during the pandemic, driven by intersecting demographic and behavioral factors. Despite converging urban-rural prevalence rates, distinct decision-making drivers necessitate context-specific interventions, including strengthened pharmacy regulation in rural areas, tailored education programs for high-risk groups, and insurance system reforms to disincentivize self-medication. Full article

High unemployment rates, inaccessible housing markets, and funding challenges create barriers to finding suitable housing for adults with Autism Spectrum Disorder (ASD) who have less obvious support needs, also known as autistic adults. While public and community housing services in Aotearoa New Zealand (AoNZ) may be an option, a lack of accessible designs leaves families uncertain about future care options. This paper, part of the MBIE-funded Public Housing and Urban Regeneration: Maximising Wellbeing research programme in partnership with registered Community Housing Provider, Te Toi Mahana (TTM), takes an exploratory approach to ask how public and community housing can support and help enable semi-independent living for autistic adults. It investigates how design elements—such as dwelling layouts, material choices, colour schemes, lighting, acoustics, shared and community spaces, and external environments—impact the wellbeing of autistic adults. By extension, insights may also inform private housing design. The study focuses on autistic adults who may be considered ‘mid-to-high’ functioning or those who have been previously diagnosed with Asperger’s Syndrome, whose housing needs are often overlooked. It develops guiding principles and detailed guidance points for public and community housing, informed by the literature, case studies, and data from a photo elicitation study and interviews undertaken with autistic adults in AoNZ. These guiding principles are tested through the speculative redesign of a large TTM site in Newtown, Wellington, AoNZ. Findings should be of interest to government agencies, housing providers, architects, stakeholders, and others involved in shaping the built environment, as well as autistic adults and their supporters, both in AoNZ and internationally. Full article

Background/Objectives: Systemic sclerosis (SSc) is a multisystemic chronic autoimmune disease, which leads to disability and possibly early retirement. The objective of our study was to explore the associations between employment status (ES) and demographic, clinical and functional features in a single-center EUSTAR cohort. Methods: Consecutive patients with SSc examined between November 2011 and June 2023, who were under the age of retirement in our country (62 years for women, 65 for men at the time), were included. All patients underwent a comprehensive clinical assessment and filled in a work assessment questionnaire as well as two validated health-related questionnaires: the Scleroderma Health Assessment Questionnaire (SHAQ) and the Duruoz Hand Index (DHI). Associations between ES and potential predictors (education level, disease characteristics, work conditions, SHAQ and DHI) were tested using logistic regression adjusted for age and gender. Results: Ninety-one patients (mean ± SD age 53.7 ± 11.8 years, twenty-two with diffuse skin involvement, fifty-six with a history of digital of digital ulcers (DUs)), were included. Only 22 patients were still employed, while 69 were retired, of which 38 retired because of SSc. Among the employed, nine performed manual labor, nine spent many hours standing and three had to work in a cold environment. When potential predictors were tested separately, adjusted for age and sex, patients with higher education (OR (95% CI) 11.36 (2.03–63.36), p = 0.006) and no history of digital ulcers had higher odds of being employed. The presence of joint contractures and weightlifting as a work demand were associated with unemployment. In a multivariable model, higher education (OR 5.91, 95% CI 0.97–36.09, p = 0.054 and younger age (OR 0.90, 95% CI 0.85–0.96, p = 0.001) were independently associated with continued employment. High school education did not show a significant effect (OR 0.089, 95% CI 0.015–0.530, p = 0.008). Patients with a history of digital ulcers had the lowest employment rates compared to those with no digital ulcer history. No significant associations were found between employment status and SHAQ or DHI scores. Conclusions: SSc is associated with significant work disability and early retirement. Higher education, the lack of Dus and younger age were highly associated with staying employed. Given the rarity of SSc, we consider that our good sample size (n = 91) reflects disease prevalence, but results should be tested in other studies and the single center should be considered when interpreting generalizability. Full article

The goal of this research is to analyze the mean squared error (MSE) of the kernel estimator for the conditional hazard rate, assuming that the sequence of real random vector variables ${\left(U_n\right)}_{n\in \mathbb{N}}$ satisfies the quasi-association condition. By employing kernel smoothing techniques and asymptotic analysis, we derive the exact asymptotic expression for the leading terms of the quadratic error, providing a precise characterization of the estimator’s convergence behavior. In addition to the theoretical derivations and a controlled simulation study that validates the asymptotic properties, this work includes a real-data application involving monthly unemployment rates in the United States from 1948 to 2025. The comparison between the estimated and observed values confirms the relevance and robustness of the proposed method in a practical economic context. This study thus extends existing results on hazard rate estimation by addressing more complex dependence structures and by demonstrating the applicability of the methodology to real functional data, thereby contributing to both the theoretical development and empirical deployment of kernel-based methods in survival and labor market analysis. Full article

Well-being is an important goal pursued by humans, and the living environment has a profound impact on various aspects of human health. The objective of this study is to explore the mechanism by which the built environment affects the well-being of residents, specifically how multiple, distinct domains of life satisfaction mediate the effects of diverse built environment features on well-being—a nuanced pathway not yet comprehensively examined. Based on questionnaire data collected from 22 statistical districts in Macau, with a sample size of 1313 individuals, a multilevel linear regression model and mediation analysis were applied (model R² ≈ 47%). When leisure satisfaction is used as a mediator variable alone, the explanatory power of the original model increases the most (from 7.6% to 32%). Complete Mediation via Specific Domains: Health satisfaction fully mediated the effects of intersection density (p < 0.05) and bus stop accessibility (p < 0.05). All four satisfaction domains collectively fully mediated income diversity (Shannon index, p < 0.01). The 14 built environment metrics (5 socioeconomic, 9 morphological) exhibited differential mediation mechanisms: while transportation-related metrics (intersection density, bus stops) primarily operated through health/social satisfaction, diversity indices (income, education, land use) and unemployment rate engaged all satisfaction domains. Some variables showed partial mediation through various satisfaction pathways (p < 0.01–0.05). These findings underscore the necessity of considering multidimensional life satisfaction as critical pathways in urban well-being research and policy. Full article

Since Shannon’s pioneering work, the concept of entropy has been used in many major scientific fields. It is therefore a universal concept but also defined in different ways. Entropy is used in studies of system complexity and to investigate the information content of probability distributions. One of the areas of its applications is human lifespan, i.e., the link between entropy and the methods of survival analysis. These methods are also used in assessing the duration of any socio-economic phenomenon. The aim of this article is to assess the market situation on the basis of the entropy of duration in unemployment. This study determines the Shannon entropy, residual entropy, past entropy, and cumulative residual entropy under the assumption of an exponential distribution of duration. Ward’s hierarchical clustering and the Dynamic Time Warping measure were used to analyse entropy and its relationship with the unemployment rate. It was shown that not all of the analysed models determine the entropy of duration in unemployment well for an exponential distribution. It was substantiated that there is a similarity between the formation of the entropy of duration in unemployment and the registered unemployment rate. It is shown that high unemployment rates in the labour market are a destabilising element of the labour market, more so than crises. Full article

This study investigated the determinants of the Healthcare Quality Index (HQI) in Saudi Arabia over the period from 1990 to 2024. It specifically analyzed the impact of six key variables: Medical Insurance Penetration Rate (MIPR), Gross Domestic Product per Capita (GDP), Unemployment Rate (UR), Inflation Rate (IR), Government Healthcare Expenditure as a Percentage of GDP (GHE), and Foreign Direct Investment in the Healthcare Sector (FDI). Utilizing the Autoregressive Distributed Lag (ARDL) and Vector Error Correction Model (VECM) techniques, this research explored both the short-term dynamics and the long-term equilibrium relationships among these time-series variables, while also accounting for cointegration and potential endogeneity. This study contributes to the existing literature by applying the ARDL and VECM methodologies to comprehensively analyze the combined impact of these factors on HQI within the unique economic and social framework of Saudi Arabia, addressing a notable void in this specific context and exploring both transient fluctuations and sustained equilibrium relationships. The key findings revealed distinct influences across time horizons. In the short term, GDP and GHE significantly and positively affect HQI, whereas UR and IR demonstrate a significant negative impact. Short-term impacts of MIPR and FDI are found to be positive but not statistically significant. The long-term analysis indicates that MIPR, GHE, and FDI have a significant positive influence on HQI, while IR maintains a significant negative impact. GDP and UR effects are not statistically significant in the long term. Further analysis using Granger causality tests and VECM confirmed that MIPR, GDP, GHE, and FDI collectively Granger-cause HQI, with government healthcare expenditure playing a crucial role in correcting short-term deviations toward long-term equilibrium. This study concludes that long-term strategies focusing on expanding insurance coverage, increasing government healthcare investment, and attracting foreign direct investment are vital for significantly enhancing healthcare quality in Saudi Arabia. The sustained positive influence of these factors and the critical role of government spending in maintaining long-term stability underscore their importance for effective healthcare policy. While emphasizing these long-term drivers, policymakers should also remain cognizant of the significant negative short-term fluctuations caused by unemployment and inflation. Full article

This study investigates the dynamic relationships between climate change and financial stability in South Africa by employing a Bayesian vector autoregression model (BVAR). Using data from 1991 to 2022, we examine the impact of carbon emissions, adjusted savings, renewable energy consumption, lending interest rates, and unemployment on financial stability. Our findings indicate that carbon emissions, adjusted savings damaged by carbon dioxide emissions, renewable energy consumption, and unemployment significantly erode financial stability. Impulse response functions reveal that shocks to carbon emissions, lending interest rates, and unemployment have lasting effects on financial stability. Forecast error variance decomposition analysis shows that external factors, particularly carbon emissions and lending interest rates, increasingly drive uncertainty in forecasting financial stability over time. The study’s results support the Financial Instability Hypothesis and the Diamond–Dybvig model, highlighting the importance of considering climate-related risks in financial stability analysis. The findings have significant implications for policymakers and financial regulators seeking to promote financial stability and mitigate climate-related risks in South Africa. Full article