Search Results (88)

This article examines how research-and-development (R&D) expenditure—as a share of GDP—both in total and disaggregated by sector (business enterprise and government)—shapes key socioeconomic outcomes in the EU-27. Drawing on Eurostat panel data for 2013–2022, we estimate fixed- and random-effects models with sector-specific lags. Business R&D expenditure is associated with lower female and male unemployment and faster GDP growth. Government R&D expenditure, by contrast, widens the gender pay gap and dampens GDP per capita after two years, although it attracts foreign direct investment in the short and medium term. The diminishing impact of R&D over time underscores the need for policies that sustain innovation benefits. Full article

This study examined the socioeconomic and veterinary cost factors influencing dog abandonment and adoption outcomes across 162 regions in the Republic of Korea from 2021 to 2023. Unlike prior research, this study distinguished between intentionally abandoned dogs and those lost and subsequently returned to their owners, normalizing abandonment data by population. Using publicly available regional data and spatial regression models, we found that the number of people receiving unemployment benefits was consistently and negatively associated with the number of dog abandonments per 100,000 residents, which was normalized by total population to avoid potential errors. Rabies vaccination costs were also negatively associated with abandonment. In contrast, comprehensive income tax amounts—a proxy for regional wealth—were positively correlated with the percentage of dog abandonments reported in 2021 and 2023. Spatial Lag Models accounted for over 50% of the variance in the number of dog abandonments, confirming spatial dependence and highlighting the importance of geographically targeted animal welfare interventions. However, spatial patterns in adoption were less consistent. These findings highlight the importance of incorporating economic and spatial considerations into the design of public policies and shelter strategies to mitigate dog abandonment and enhance adoption outcomes. Full article

The concept of inclusive growth highlights that enhancing human development requires ensuring not only sustainable economic growth but also that its benefits are widely shared. In turn, the problem of skills/educational mismatch looms large because of its (negative) consequences for individual and societal well-being. Against this background, this article studies some effects of skills/educational mismatch on inclusive economic growth. More concretely, it focuses on the relationships between vertical educational (mis)match and some macro characteristics, such as the level of unemployment and poverty indices. Theoretically, in searching for a more comprehensive understanding of skills/educational mismatch, the article draws on the heuristic potential of the capability approach. Empirically, this study relies on data from the 11th round of the European Social Survey, carried out in 2023/2024, and official statistical sources and has applied correlations for the analyses. This study’s findings show that the vertical educational match can be viewed as a sign of inclusive growth. They further reveal that the effects of skills/educational (mis)match at the societal level vary among different occupational groups. Finally, the obtained results demonstrate that vertical—either above or below—educational mismatch is related to capability deprivation at a societal level. Full article

Measuring financial performance is pivotal not only for assessing a firm’s current health but also for informing strategic decisions that shape its long-term trajectory. This study investigates how macroeconomic volatility affects the firm profitability across five major sectors in Türkiye—industrial manufacturing, food, beverage and tobacco, chemicals and plastics, technology, and energy—during the turbulent period from 2016 to 2023. Using return on assets (ROA) and return on equity (ROE) as performance indicators, we apply panel data regression to test the impact of inflation, interest rates, unemployment, and a novel Macroeconomic Stress Index (MSI), which combines inflation and exchange rate volatility. The results reveal significant sectoral differences: firms in chemicals and manufacturing outperformed others in ROA, likely benefiting from export incentives and scale efficiencies, while energy and food sectors underperformed, constrained by regulations and cost rigidity. Notably, MSI showed a consistent and significant positive effect on both ROA and ROE, suggesting that many firms responded to macroeconomic stress by restructuring operations and improving efficiency. In contrast, interest rates had a strong negative effect on profitability, confirming the sensitivity of firms to financing costs. These findings underscore the need for targeted sector-level policy support and highlight the importance of internal adaptive capabilities in maintaining the firm’s performance under sustained economic stress. Full article

Background/Objective: To address the growing demand for mental health services, Nova Scotia Health introduced the Rapid Access Stabilization Program (RASP) through its Mental Health and Addictions Program (MHAP) in April 2023. RASP is designed to help reduce long wait times, frequent emergency department visits, and admissions to provide early intervention for individuals experiencing mental health problems. The RASP focuses on rapid access and early mental health intervention, aiming to prevent the worsening of patients’ symptoms, improve access to psychiatric care, and reduce service pressures on programs like the Community Mental Health Program (CMHP), which provide more extended, ongoing mental health support. This study compared participants’ sociodemographic and clinical profiles in the RASP and the CMHP. Methods: Data were collected from 1392 participants accessing mental health support either through the RASP or CMHP. A comparative analysis of sociodemographic factors (e.g., age, education, and income) and clinical characteristics (e.g., depression, anxiety, resilience, and substance use) was conducted. Chi-square tests and independent sample t-tests were used to evaluate the mean differences between the groups. Results: Significant sociodemographic and clinical differences emerged between the RASP and CMHP participants. The RASP group was older (M = 40.10 vs. 34.52 years) and more socioeconomically stable, with higher rates of employment (55.3% vs. 47.9%) and homeownership (36.5% vs. 17.7%). In contrast, the CMHP group had higher unemployment (25.7% vs. 16.5%) and lower income levels, with 47.5% earning <CAD 29,590 compared to 30.3% in the RASP group. Clinical profiles differed markedly: depression was more prevalent in the RASP (48.2% vs. 19.3%), whereas the CMHP had higher rates of psychosis (10.6% vs. 2.5%) and substance use disorder (7.8% vs. 1.9%). The RASP participants exhibited higher anxiety (GAD-7: M = 14.17 vs. 11.81) and depression symptoms (PHQ-9: M = 16.62 vs. 14.20) but lower resilience (BRS: M = 2.47 vs. 2.77). The CMHP participants had more adverse childhood experiences (ACE: M = 3.92 vs. 3.16) and lower suicidal intent (81.4% vs. 99.4% had no intention to act). Conclusions: The findings highlighted the unique profiles between the RASP and CMHP participants, suggesting the need for program-specific interventions. While the CMHP participants may benefit from integrated social support and trauma-informed care, the RASP participants may require cognitive behavioral therapy and resilience-building interventions. Tailoring mental health services to meet these unique needs could enhance program effectiveness and patient outcomes across both groups. Full article

Sustainable development is a tripartite game among the central (CG) and local governments (LGs) and enterprises, with economic factors as key drivers. China consumed about 16.2 million metric tons during this period, accounting for approximately 61% of global consumption, thereby reinforcing its position as the world’s leading copper consumer. Seeking a balance of acceptable interests among the three parties may be a feasible method to explore the sustainable development of China’s copper enterprises (CEs). Therefore, based on evolutionary game theory, we construct a three-party evolutionary game model. Using the financial data of Chinese CEs and actual survey data on the CG and LGs, we identified 31 environmental impact parameters from the CG, LGs, and CEs. Then, we used MATLAB R2023b to simulate an evolution model and determined the influence of various factors on the evolutionary stable state. The results show that LGs, as local managers, have implemented more direct and expedited regulations than the CG. Enterprises with less brand impact frequently face difficulties in complying with governmental regulatory demands. When interests are balanced, 30% of enterprises cannot meet standards within 40 months, which may cause 500 small and medium-sized enterprises to stop production, thus resulting in high unemployment costs for LGs. A scenario analysis evaluates the economic benefits of environmental measures based on evolutionary game results. The results show that the introduction of advanced hydrometallurgy technology has the highest economic benefits; after 5 years, the economic benefits of China’s entire copper industry will reach CNY 147.2 billion. Full article

This paper examines the societal, demographic, and health-related determinants of online stress management information-seeking (OSMIS) behavior in Hungary. We processed the International Social Survey Program: Health and Healthcare (n = 1008) dataset of 2021. Relationships between variables were assessed using weighted multiple logistic regression. The bootstrapping method was applied to gauge the robustness and reliability of the estimates. Subgroup analyses were also utilized to explore potential confounding effects between OSMIS behavior and various socioeconomic and health-related lifestyle factors. Empirical findings indicate that socially excluded strata were the most likely to seek online stress management information to cope with stressful situations. OSMIS behavior was significantly associated with divorced marital status (OR = 3.13; 95% CI: [1.92–5.17]), unemployment (OR = 2.22 [1.64–2.99]), living in a rural village (OR = 1.39 [1.12–1.93]), and distrust in the healthcare system (OR = 2.03 [1.33–3.11]). During the COVID-19 pandemic, the concept of techquity played a pivotal role in Hungary, bridging gaps in health access. Policymakers, healthcare practitioners, and digital health developers may harness our results to enhance digital health tools within integrated healthcare systems, prioritizing equitable access to ensure that marginalized populations can fully benefit from the advantages of techquity and digital inclusion. Full article

Over the past 30 years, Swedish labor market politics has swayed towards stronger workfare tendencies, emphasizing activation requirements for unemployed individuals to access welfare benefits. This process aligns with broader neoliberal reforms, fostering an individualistic view of unemployment characterized by personal responsibility for employability. In 2023, the Swedish Public Employment Service (PES) published a report addressing the needs of and solutions for long-term unemployed individuals ‘distant from the labor market’ (Sw. personer långt från arbetsmarknaden), marking the first formal use of this term as the main adhesive category in a political document. This paper examines the construction of the subject position ‘distant from the labor market’, investigating how it delineates and differentiates subgroups within the unemployed population, how this subgroup is understood in relation to other actors, and how discursive frameworks imbue this category with various meanings. Lastly, the paper discusses the categorization in relation to the current developments in the Swedish welfare system, arguing that the formalization of this category should be understood in relation to parallel political processes, such as proposals for a duty of activity for the unemployed, suggesting how this points to a way forward defined by neoliberal tendencies and welfare conditionality. Full article

The advancement of digital technologies has become a transformative driver of economic development. Digitalisation is central to the global economy, enhances productivity, drives innovation, and promotes inclusive growth. Despite this potential, South Africa faces persistent challenges such as skills shortages, unemployment, poverty, and socioeconomic inequality. This study investigates the role of digitalisation in advancing economic complexity, human capital development, and gross national income in South Africa. A digitalisation index, constructed through Principal Component Analysis, ARDL models, and Granger causality analysis, provides insights into the short- and long-term impacts and causal relationship. The findings reveal that digitalisation and education significantly enhance human capital development in the long run, with digital infrastructure also driving immediate gains. For the gross national income model, digitalisation and education pose short-term pressures due to development expenditures, while institutional quality plays an important role in sustaining income. Economic complexity benefits positively from digitalisation over the long term, though short-term impacts stress the role of governance quality and infrastructure. Causality analysis further shows the interconnectedness of these variables, with digitalisation advancing economic complexity and human capital driving national income, reinforcing digitalisation. The results call for policies that align short-term developmental priorities with long-term sustainability. Investments in digital infrastructure, accessible education, and institutional frameworks are critical for building a skilled labour force while enhancing economic complexity and maintaining financial stability. Full article

Objectives: Whiplash trauma is a worldwide significant public health issue, with post-collision chronic pain and physical and mental disability; the prevalence of whiplash trauma in the Japanese general population is estimated at 1.2% and in the Danish general population the whiplash condition has been reported to be 2.9%. Pre-collision welfare benefits and illness perceptions have been found to predict poor recovery after whiplash trauma. In this study, we examined whether illness perceptions measured shortly post-collision moderated the effect of welfare benefits five years before the collision on neck pain and neck-related disability one-year post-collision. Methods: Patients consulting emergency rooms or general practices with neck pain after acute whiplash trauma were invited to complete questionnaires during the week after the collision and at three and 12-months post-collision. Further, we obtained register data on the number of weeks on three types of welfare benefits (sick leave benefits, unemployment benefits, and social assistance benefits) for a five-year period before the collision. Multiple logistic regression was applied. Results: 740 patients were included. We did not find a significant moderating effect of illness perceptions on the association between pre-collision welfare benefits and chronic neck pain and related disability. However, there was a trend towards illness perceptions at baseline and at the three-month follow-up having a moderating effect on the relationship between long-term sick leave and neck pain one year after the whiplash collision. Conclusions: Regarding long-term sick leave, we might have overlooked a substantial moderating effect due to methodological matters and recommend a replication of this study on a larger sample, also focusing on other recovery outcomes. Full article

West Virginia, home to approximately 1.77 million residents, has been grappling with significant economic challenges characterized by persistent poverty and sluggish growth. Despite ongoing development efforts, the state’s Gross State Product (GSP) has seen only a modest increase of 0.1% over the past five years, reaching USD 71.7 billion, while the unemployment rate remains at 4.0%. The annualized employment growth rate of 0.7% lags behind the national average, and only about 54% of West Virginia’s adult population is either employed or actively seeking employment, resulting in one of the lowest labor force participation rates in the nation. In contrast, certain industrial sectors, such as healthcare, social assistance, retail trade, and accommodation and food services, have shown intermittent growth at the county and regional levels. To explore the unique characteristics and significance of these regions in relation to employment growth, this study examines regional employment patterns in West Virginia from 2001 to 2020, focusing on the main regions of the state: Metro Valley, Mid-Ohio Valley, New River/Greenbrier Valley, Mountain Lakes, and Potomac Highlands. Utilizing shift-share and location quotient ($LQ$) analyses, this research identifies the sectors driving regional employment and assesses their performance. Key findings reveal strong sectoral performance in mining, manufacturing, and finance in the Mid-Ohio Valley; wholesale trade, transportation, and utilities in the Metro Valley; agriculture and administrative services in the New River/Greenbrier Valley; agriculture and manufacturing in the Potomac Highlands; and scientific services, healthcare, and utilities in the Mountain Lakes region. Based on these insights, this study recommends targeted policy interventions to address regional disparities, enhance sectors with significant short- and long-term benefits, and foster balanced economic development across the state. Full article

This study investigates the profound and multifaceted impacts of Artificial Intelligence (AI) and geopolitical developments on global dynamics by 2040. Utilising a Delphi process coupled with probabilistic modelling, the research constructs detailed scenarios that reveal the cascading effects of these emerging forces across economic, societal, and security domains. The findings underscore the transformative potential of AI, predicting significant shifts in employment patterns, regulatory challenges, and societal structures. Specifically, the study forecasts a high probability of AI-induced unemployment reaching 40–50%, alongside the rapid evolution of AI technologies, outpacing existing governance frameworks, which could exacerbate economic inequalities and societal fragmentation. Simultaneously, the study examines the critical role of geopolitical developments, identifying increased nationalisation, the expansion of conflicts such as the Russia–Ukraine war, and the strategic manoeuvres of major powers like China and Israel as key factors that will shape the future global landscape. The research highlights a worrying lack of preparedness among governments and societies, with a 10% probability of their being equipped to manage the complex risks posed by these developments. This low level of readiness is further complicated by the short-term orientation prevalent in Western businesses, which prioritise immediate returns over long-term strategic planning, thereby undermining the capacity to respond effectively to these global challenges. The study calls for urgent, forward-looking policies and international cooperation to address the risks and opportunities associated with AI and geopolitical shifts. It emphasises the need for proactive governance, cross-sector collaboration, and robust regulatory frameworks to ensure that the benefits of technological and geopolitical advancements are harnessed without compromising global stability or societal well-being. As the world stands on the brink of unprecedented change, the findings of this study provide a crucial roadmap for navigating the uncertainties of the future. Full article

Unemployment is the most important problem that countries need to solve in their economic development plans. The uncontrolled growth and unpredictability of unemployment are some of the biggest obstacles to economic development. Considering the benefits of technology to human life, the use of artificial intelligence is extremely important for a stable economic policy. This study aims to use machine learning methods to forecast unemployment rates in Turkey on a monthly basis. For this purpose, two different models are created. In the first model, monthly unemployment data obtained from TURKSTAT for the period between 2005 and 2023 are trained with Artificial Neural Networks (ANN) and Support Vector Machine (SVM) algorithms. The second model, which includes additional economic parameters such as inflation, exchange rate, and labor force data, is modeled with the XGBoost algorithm in addition to ANN and SVM models. The forecasting performance of both models is evaluated using various performance metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). The findings of the study show how successful artificial intelligence methods are in forecasting economic developments and that these methods can be used in macroeconomic studies. They also highlight the effects of economic parameters such as exchange rates, inflation, and labor force on unemployment and reveal the potential of these methods to support economic decisions. As a result, this study shows that modeling and forecasting different parameter values during periods of economic uncertainty are possible with artificial intelligence technology. Full article

The surge in opioid use disorder (OUD) over the past decade escalated opioid overdoses to a leading cause of death in the United States. With adverse effects on cognition, risk-taking, and decision-making, OUD may negatively influence financial well-being. This study examined the financial health of individuals diagnosed with OUD by reviewing financial beliefs and financial behaviors. We evaluated quality of life, perceptions of financial condition during active use and recovery, and total debt. We distributed a 20-item survey to 150 individuals in an outpatient treatment program for OUD in a large metropolitan area, yielding a 56% response rate. The results revealed low overall financial health, with a median debt of USD 12,961 and a quality-of-life score of 72.80, 9.4% lower than the U.S. average (82.10). Most participants (65.75%) reported improved financial health during recovery, while a higher majority (79.45%) worsened during active use. Unemployment affected 42% of respondents, and 9.52% were employed only part-time. Regression analysis highlighted a strong association between lack of full-time employment and a lack of financial advising with total debt. High financial anxiety and active use were associated with lower quality of life. Individuals with OUD may benefit from financial interventions, resources, and counseling to improve their financial health. Full article

Social media recruitment and online surveys are valuable tools in social science research, but their effectiveness in reaching seldom-heard victims of gender violence in low-middle income (LMI) countries is under-explored. This empirical study aims to: (1) describe violence and abuse experiences and (2) assess the benefits and limitations of using social media to document violence against women and girls (VAWGs) in a LMI country to render visible the experiences of potentially isolated victims. A total of 453 Iranian women (aged 14–59, mean = 28.8, SD = 8.04) responded to an Instagram invitation for a study on women’s health and violence exposure from February 2020 to January 2022. The questionnaire covered general gendered abuse, domestic violence (DV), and forced unemployment. The analysis was performed using Stata 17. Nearly all participants reported abuse, including sexual (85.0%), psychological (83.4%), and technology-facilitated (57.4%) abuse, with 77.4% experiencing multiple forms. The street (62%) and home (52.8%) were common abuse locations. The perpetrators included known individuals (75.9%) and strangers (80.8%), with 56.7% reporting abuse by both. DV was reported by 72.6%, mainly involving psychological (73.1%), physical (53.4%), and/or sexual (17.2%) violence, with fathers (47.8%), husbands (42.7%), and brothers (40.2%) as frequent perpetrators. A quarter reported forced unemployment. Those experiencing DV and/or forced unemployment showed higher depression levels, suicidal ideation, and lower marital satisfaction. The study suggests using social media recruitment for VAWG research but cautions against overgeneralising from these data. Full article