Search Results (52)

This article examines labor market dynamics in Bulgaria, Italy, and the United Kingdom by integrating demographic pressures, wage and labor cost adjustment, redistribution mechanisms, inequality outcomes, and digital readiness into a single comparative framework. This study first applies hierarchical clustering to a harmonized EU country panel for 2017–2024, using GDP per capita in PPS, average annual wage, and unemployment rate to position the three countries within the European convergence space and income–labor cost groupings. The results show that Bulgaria belongs to a low-income, fast-converging group, with nominal wages and hourly labor costs more than doubling, strong real-wage growth from a low base, and an improving price level index. At the same time, unemployment fell to below the EU average, yet income inequality remains persistently high. Italy represents a high-income but slow-growing labor market, in which real wages have declined, and labor costs per hour remain above the EU mean with a significant non-wage component. Unemployment remains relatively elevated, indicating divergence in workers’ purchasing power despite high income levels. The UK has labor costs in the mature high-income range, low unemployment, and the lowest tax wedge for low-wage workers, but with relatively high and volatile inequality. This study shows that wage dynamics, labor cost composition, and tax–benefit structures jointly mediate the translation of macroeconomic performance into household outcomes, generating distinct policy trade-offs across the three labor market configurations. Digital indicators further suggest that income level is not a sufficient predictor of digital engagement and that the observed aggregate labor market trends do not indicate a sharp employment contraction contemporaneous with the diffusion of technical innovations, such as generative AI. Full article

Income level is a key indicator of the standard of living and the economic efficiency of undertaken activities. This paper aims to evaluate the earnings of Polish dairy farmers compared to those in other economic sectors between 2005 and 2022. The analysis covered 1688 family-run farms that participated continuously in the FADN system throughout the study period, with particular emphasis on farms that expanded their dairy cow herds. The remuneration for the labour of farmers and their families was estimated ex post by subtracting the opportunity costs of owned land and capital from farm income. The alternative cost of engaging one’s own land was determined on the basis of actual rental prices for farmland occurring in the surveyed farm groups in the years analysed. This information is collected in the FADN system from which the studied group of farms was drawn. The basis for determining the alternative cost of involvement of own capital was the average interest rates on deposits for households, concluded for a period of 6 months to 1 year inclusive, reported by the National Bank of Poland. The analysed population was divided into seven groups based on the number of dairy cows maintained. The analysis focused on two three-year reference periods: 2005–2007 and 2020–2022. The results were compared with average salaries and wages in non-agricultural sectors of the economy. Structural changes in agriculture, increased productivity, and the expansion of production scale in dairy farms indicate a growing professionalisation of the sector. The rise in farm incomes during the analysed period contributed to a significant increase in the remuneration for farmers’ and their families’ labour. The highest growth in remuneration was observed among farms with the greatest production potential and scale. While in 2005–2007 the remuneration for labour in dairy farms was lower than in non-agricultural sectors, this situation changed in 2020–2022. During this latter period, the average remuneration for labour on dairy farms slightly exceeded the average salary and wages in other sectors of the economy. Full article

Graduate salaries are a significant concern for graduates, employers, and policymakers, as various factors influence them. This study investigates determinants of graduate salaries in the UK, utilising survey data from HESA (Higher Education Statistical Agency) and integrating advanced machine learning (ML) explanatory techniques with statistical analytical methodologies. By employing multi-stage analyses alongside machine learning models such as decision trees, random forests and the explainability with SHAP stands for (Shapley Additive exPanations), this study investigates the influence of 21 socioeconomic and demographic variables on graduate salary outcomes. Key variables, including institutional reputation, age at graduation, socioeconomic classification, job qualification requirements, and domicile, emerged as critical determinants, with institutional reputation proving the most significant. Among ML methods, the decision tree achieved a standout with the highest accuracy through rigorous optimisation techniques, including oversampling and undersampling. SHAP highlighted the top 12 influential variables, providing actionable insights into the interplay between individual and systemic factors. Furthermore, the statistical analysis using ANOVA (Analysis of Variance) validated the significance of these variables, revealing intricate interactions that shape graduate salary dynamics. Additionally, domain experts’ opinions are also analysed to authenticate the findings. This research makes a unique contribution by combining qualitative contextual analysis with quantitative methodologies, machine learning explainability and domain experts’ views on addressing gaps in the existing identification of graduate salary predicting components. Additionally, the findings inform policy and educational interventions to reduce wage inequalities and promote equitable career opportunities. Despite limitations, such as the UK-specific dataset and the focus on socioeconomic and demographic variables, this study lays a robust foundation for future research in predictive modelling and graduate outcomes. Full article

In this study, we analyze the relationship between economic variables influencing wages in the Dutch economy during the period 1995–2023 using the ARIMAX method. The analysis reveals that lagged wages and salaries for male workers have a strong and significant effect on current wages, while lagged wages and salaries for female workers exhibit a strong negative influence, indicating a potential gender wage gap. The current level of foreign direct investment (FDI) has a negative impact on wages, suggesting that foreign capital may not contribute to wage growth, and we noted that lagged FDI does not significantly affect current wages. These findings highlight the crucial role of past wages in shaping current wage levels and accentuate that gender disparities remain a significant factor in wage determination. Policymakers should consider addressing these gender wage differences and reassess the role of FDIs in wage growth. Full article

Background: Rising costs and demands for improved quality of care present complex challenges for existing healthcare systems. The strain on healthcare resources is exacerbated by the increasing complexity of patient conditions. The Diagnosis-Related Group (DRG) system classifies inpatients according to clinical and treatment criteria, controls healthcare expenditures, and ensures the sustainability of procedures. The cost of nursing care is included in the DRG system in the same way as other fixed costs of hospital care, but the amount of nursing care provided for the same DRG can vary widely. This study, which is based on this protocol, will aim to assess the variability of nursing costs within and across DRGs and to measure how much variability in nursing care is explained by DRGs by comparing nursing care delivery in acute care hospitals with the DRG reimbursement system in Italy. It is necessary to develop a specific protocol to ensure systematic and consistent data collection at the national level. Methods: A multicenter retrospective cross-sectional study will be conducted. A random sample of five public Italian hospitals will be enrolled. Patients included in medical or surgical DRGs, hospitalized and discharged in 2022 will be included. Data will be collected retrospectively from two sources: hospital discharge records and nursing records. Inferential statistics will be used to assess the variability of nursing time and costs across hospitals and DRGs. Nursing costs will be determined by several factors, including time spent on nursing activities and the hourly wages of nursing staff. The time needed to complete each activity will be estimated by a convenience sample of nurses from the hospitals included in this study. The annual salary of nurses will be used to calculate the nursing cost per minute, multipled by the amount of time spent per each nursing activity. The cost per patient per day of hospitalization will be calculated. Conclusions: The results of this study will shed light on the variation in nursing care across different DRGs. This understanding will guide recommendations for optimizing healthcare resource allocation and enhancing the efficiency of the DRG system in Italy. Full article

The literature associating the spread of SARS-CoV-2 with the healthcare-related, geographical, and demographic characteristics of the territory is inconclusive and contrasting. We studied these relationships during winter 2021/2022 in South Tyrol, a multicultural Italian alpine province, performing an ecological study based on the 20 districts of the area. Data about incidence, hospitalization, and death between November 2021 and February 2022 were collected and associated to territorial variables via bivariate analyses and multivariate regressions. Both exposure variables and outcomes varied widely among districts. Incidence was found to be mainly predicted by vaccination coverage (negative correlation). Mortality and ICU admission rates partially followed this distribution, while the case fatality rate was inversely correlated to average salary, and hospital admission rates increased where hospitals capacity was higher, and from the southern to the northern border of the province. These findings, besides confirming the efficacy of vaccination in preventing both new and severe SARS-CoV-2 cases, highlight that several geographical and socio-demographic variables can be related to disease epidemiology. Remote areas with wage gaps and lower access to care suffered most from the pandemic. Our findings, therefore, underly the existence of health inequity issues that need to be targeted by implementing specifically tailored public health interventions. Full article

The objective of the study was to ascertain the purchasing power potential of the average gross salary in the real estate market. The study area involved the European Union (EU) member states from 2008 to 2022. The research was based on the following data: average earnings for a full-time job, housing market transaction prices, and housing rental prices in the country. The analysis demonstrated that the average European must save for nearly six years for the purchase of their own apartment. Over the period from 2015 to 2022, the purchasing power of the monthly wage decreased in 20 of the 26 countries included in the survey. A recent study has demonstrated that 31% of the EU’s residents maintain households in rented housing. The study revealed that in the capital cities of six of the twenty countries surveyed, rent constitutes more than half of the average salary. Warsaw, the most expensive capital city, requires more than 93% of the average salary to be spent on rent. Full article

Following the COVID-19 pandemic crisis, the emphasis on digitization and robotization has grown at an unprecedented rate in the global economy, resulting in significant changes to the labour market composition and increasing the value of digital skills. The aim of this article is to emphasize the ways in which people’s digital abilities and appetite for online activities are connected to job productivity (salary levels) and to determine which individual internet-based digital skills are genuinely important and correlated with better wages. We employed a Principal Component Analysis (PCA-type factorial analysis) with orthogonal rotation to gain a general understanding of the main components that synthesize the digital capabilities of individuals from the European countries analyzed. We decreased the dimensionality of our initial dataset to two major components, namely comprehensive online skills and digital social and media skills, keeping more than 80% of the overall variability. We then evaluated the potential association between the two created components and the average hourly wages and salaries. Since the end of the COVID-19 pandemic, we have observed an important shift in the impact of digital and internet skills on the job market in Europe. Thus, the development of comprehensive internet skills is highly correlated with individuals’ more effective integration into the labour market in Europe in general and the EU in particular, evidenced by better wage and salary levels (r = 0.740, p < 0.001). On the other hand, we found no correlation between the possibility of obtaining higher salaries for employees and the second component, digital social and media skills. The novelty of our research lies in its specific focus on the unique and immediate impacts of the pandemic, the accelerated adoption of digital skills, the integration of comprehensive individual internet skills, and the use of the most recent data to understand the labour market’s characteristics. This new approach offers fresh insights into how Europe’s workforce could evolve in response to unprecedented challenges, making it distinct from previous studies of labour market skills. Full article

This study investigates the nuanced influence of Foreign Direct Investments (FDIs) on wage dynamics among Croatian workers, specifically examining the differential effects on male and female salaried employees. The authors employed statistical indicators and regression analysis, utilizing data from reputable sources, such as UNCTAD and the World Bank, to assess the dependency of wages on FDIs at time periods n and n − 1. By focusing on these temporal dynamics, the study aims to capture potential changes in the relationship between wages and FDIs, aligning with the total quality management (TQM) principle of systematic analysis. The findings highlighted the differential impact of FDIs on wage evolution for male and female workers, underscoring the importance of integrating gender-sensitive strategies within quality management frameworks. Full article

Micro and large-sized enterprises are important elements to enhance the economic growth of any country, and even more so for developing countries such as Mexico. These enterprises highly contribute to job generation, competitiveness, and gross domestic product, factors that are important for the developing of a nation. The aim of this paper is to study the impact of human capital investments in the efficiency of the 21 economic activity subsectors for micro and large-sized enterprises in the Mexican manufacturing industry between 2009–2021. The database come from Mexico Annual Manufacturing Industry Survey. Four Data Envelopment Analysis models are developed to study the relationship between annual average working days, annual average wages, and annual average investment in training with average sales per year. Data indicate that, most of the micro-sized enterprises of the Mexican manufacturing sector do not invest in human capital training, contrary to their large-sized enterprises. The results show that investing in human capital training increase sales and wages in micro-sized enterprises of the Mexican manufacturing industry, but it is not evident in large-size enterprises of the Mexican manufacturing industry. The calculation of the economic activity subsectors efficiencies using the developed Data Envelopment Analysis models indicate that all the economic activity subsectors with scale efficiency equal to one optimally invest, and the average amount of investments in human capital training needed to increase the global and pure technical efficiencies of the others are calculated with the developed Data Envelopment Analysis models. In the three main economic activity subsectors of the Mexican manufacturing industry, a significant increase—in 83.33% of cases—in wages and salaries is seen in both micro and large-sized enterprises. Particularly, the results indicate that the Chemical industry economic activity subsectors show the highest efficiency in both micro and large-sized enterprises when the human capital training variable is present. This paper demonstrates the importance of investing in human capital to enhance the efficiency of micro and large-sized enterprises. Full article

With a focus on seafood industries, this study provides a framework for economic contribution assessments, outlines Virginia’s seafood supply chain components, and evaluates the direct, indirect, and induced economic impacts of Virginia’s seafood industry in 2019. Utilizing an analysis-by-parts method in IMPLAN, primary expenditure data from watermen, aquaculture farmers, processors, and distributors were collected through surveys. The efficacy of obtaining primary data through stakeholder surveys heavily relies on the investigator’s interpersonal skills to establish trust and elucidate the study’s benefits, particularly its potential to inform policy decisions. In 2019, the Virginia seafood industry’s estimated total economic contributions amounted to USD 1.1 billion, supporting 7187 individuals. This impact encompasses 6050 direct jobs, 523 indirect jobs, and 614 induced jobs, primarily benefiting watermen and coastal communities. Furthermore, the industry’s influence extends beyond its immediate economic sphere, supporting diverse sectors such as polystyrene foam manufacturing, boat building, sporting and athletic goods, and commercial and industrial machinery. Wages and salaries disbursed throughout the seafood supply chain ripple to Virginia’s economy, benefiting nondepository credit intermediation, owner-occupied dwellings, and real estate sectors. Future research focusing on seafood sales in restaurants and retail outlets will complete the understanding of the seafood industry’s broader economic impact on the state. Full article

The content of this paper presents the research results of a three-year research project in which a multi-criteria evaluation model (according to the DEX methodology) was developed for the evaluation of three different food sectors (represented by a cattle breeding chain, a pig farming chain, and a milk production chain) with added value in Slovenia. Indicators for the assessment of the economically, socially, and environmentally sustainable development of food chains were taken into account. The data for the analysis, such as prices and costs of food, wage levels by sector, food miles and others, were obtained from various public services between 2020 and 2023. The final qualitative assessment of the food sectors was uniform (“average”), while the longest analysis of the results using the plus-minus-1 analysis method showed the reasons for such an assessment in individual sectors (such as the ratio between the price of agricultural products and the price of agricultural inputs is poor, the ratio between average gross salary in the individual food sector and gross salary in the agricultural sector is poor, etc.). In addition to the results already mentioned, recommendations or suggestions for building a sustainable food chain were made using the results of the modelling. The research results contributed to a better understanding of the importance of stable relationships between different groups of indicators and later showed their importance for improving the functioning of agri-food chains. The results of the research will help various stakeholders (such as the agricultural advisory service, decision-makers at the level of agricultural policy, researchers in further analyses, and especially the international professional public interested in various case studies from EU countries) to further analyse and plan for the organisation of the agricultural sector. Full article

Addressing food security is one of the national priorities in South Africa, enshrined under the country’s constitution, yet there is a growing percentage of households struggling to meet their food requirements. Food insecurity and malnutrition remain severe problems in rural communities and can be addressed through home gardening. This study aimed to assess the contributions of home gardens to food security in Limpopo Province. This study employed a quantitative research methodology. A total of 2043 rural households were selected using multistage stratified random sampling. The Household Food Insecurity Access Scale (HFIAS) was used to measure household food insecurity levels of home garden participants. Results showed that 46% of participants were food secure, 24% were severely food insecure, 17% were moderately food insecure and 13% were mildly food insecure. The results from the endogenous switching Poisson regression model showed that gender, household size, wage/salary, access to land, agriculture-related assistance and market distance had a positive influence on household food security of home garden participants. On the other hand, employment status and receiving any social relief had a negative association with household food security of home garden participants. The results also showed that employment status had a positive influence on the food security of home garden non-participants, while education, access to land, wage/salary and age had a negative influence. The results from average treatment effects (ATEs) showed that households that participated in home garden production had a negative and significant (p-value < 0.05) impact on household food insecurity. This study concludes that involvement in home gardening improves food security. Household food security can be enhanced through agricultural training and skills enhancement directed at increasing participation in home gardening in rural areas, thus addressing income and food security challenges. Agricultural education needs to be introduced and facilitated at school levels so that an understanding of food systems, nutrition and food security can be attained from younger age groups. Full article

In this cross-sectional descriptive study conducted in the Ratnapura district, Sri Lanka, we assessed the affordability of oral pediatric anti-infective medicines (OPAIMs). Using a modified WHO/HAI medicinal price methodology, we examined the availability, median price ratios (MPRs), mean percentage difference, and affordability of the standard treatment of the originator brand (OB) and lowest-priced generic (LPG) OPAIMs in 30 private and 2 state-owned pharmacies. The study revealed disparities in availability, with only 50% of private pharmacies offering all 11 medicinal drugs in their generic form. The MPRs of OPAIMs for OB and LPG varied, with three drugs exceeding the financially acceptable MPR of 2 (albendazole, amoxicillin, and erythromycin). The standard treatment with LPGs costs between 0.17 and 0.85 and between 0.06 and 0.28 days’ wages for the lowest daily salary of the private sector and unskilled public employees, respectively. We identified erythromycin and albendazole as having less than 50% availability in their generic form in private pharmacies. To address these findings, we recommend frequent pricing revisions based on exchange rates and associated costs, coupled with the establishment of a transparent scientific criterion to subsidize essential medicines deemed “unaffordable.” Failure to implement such measures amidst economic crises may adversely impact financial access to essential medications. Full article

In the context of the sustainability roadmap, this study presents a quantitative perspective by investigating the interconnection between foreign direct investments (FDIs) and wage dynamics to contribute to the reduction of gender inequalities. This paper focuses on Austria and Germany, two European countries with strong commitments to sustainable change, as representative cases for the analysis. The main objective is to quantify the impact of FDIs on salary trends and investigate their relationship, especially concerning gender-related aspects. This research introduces fresh insights into the existing literature by shedding light on the role of FDIs in shaping wage dynamics, particularly related to gender equality. The quantitative analysis highlights the model’s robustness, revealing that approximately 86% of wage variation is explained by the independent variable, FDIs. This statistical result suggest a linear relationship between FDIs and wages in these two countries, reaffirming the potential impact of foreign investments on wage dynamics as a base for enhancing sustainable socioeconomic progress. Full article