This study aims to analyze how public debt influences economic growth in Kosovo, using quarterly data from Q1 2008 to Q4 2022 and employing the generalized method of moments (GMM). The research reveals that there is a negative relationship between public debt and economic growth when other factors such as trade openness, total investment, current account balance, and primary balance are considered. Furthermore, the findings confirm an inverted “U-shaped” relationship between public debt and economic growth, indicating that the optimal debt level is between 27.75% and 36.2% of GDP.

Since the proposal of the low-carbon economy plan, all countries have deeply realized that the economic model of high energy and high emission poses a threat to human life. Therefore, in order to enable the economy to have a longer-term development and comply with international low-carbon policies, enterprises need to speed up the transformation from a high-carbon to a low-carbon economy. Unfortunately, due to the massive volume of data, developing a low-carbon economic enterprise management model might be challenging, and there is no way to get more precise forecast data. This study tackles the challenge of developing a low-carbon enterprise management mode based on the grey digital paradigm, with the aim of finding solutions to these issues. This paper adopts the method of grey digital model, analyzes the strategy of the enterprise to build the model, and makes a comparative experiment on the accuracy and performance of the model in this paper. The results show that the values of MAPE, MSE and MAE of the model in this paper are the lowest. And the r^2 of the model in this paper is also the highest. The MAPE value of the model in this paper is 0.275, the MSE is 0.001, and the MAE is 0.003. These three indicators are much lower than other models, indicating that the model has high prediction accuracy. r² is 0.9997, which is much higher than other models, indicating that the performance of this model is superior. With the support of this model, the efficiency of building an enterprise model has been effectively improved. As a result, developing an enterprise management model for the low-carbon economy based on the gray numerical model can offer businesses new perspectives into how to quicken the shift to the low-carbon economy.

Malaysia’s economic development strategies have evolved significantly since independence, focusing on reducing poverty, enhancing education, and integrating technology to foster sustainable growth. Despite substantial progress, challenges persist in achieving inclusive development across rural and urban sectors. This study examines the effectiveness of Malaysia’s New Economic Model (NEM) in addressing poverty and unemployment through technological and educational advancements. Employing a qualitative approach, it reviews literature on technology’s impact on economic growth, poverty alleviation, and the role of tertiary education in national development. Analysis reveals that while NEM initiatives have attracted foreign investment and improved infrastructure, gaps remain in educational access and technological self-reliance. The findings underscore the need for targeted policies that enhance educational outcomes, promote inclusive technology adoption, and address structural inequalities to achieve sustainable economic development. Recommendations include bolstering vocational training, enhancing rural infrastructure, and fostering public-private partnerships in technology innovation to ensure equitable economic progress.

The female labor force participation holds significant implications for various aspects of society, the economy, and individual lives. Understanding its significance involves recognizing the multifaceted impact of women’s participation in the workforce. In this context, the current study investigates the factors influencing the female labor force participation rate in Saudi Arabia while using a set of independent variables such as GDP growth, employment-to-population ratio, inflation, urban population growth, tertiary school enrollment, labor force with advanced education, fertility rate, and age dependency ratio, covering a period from 2000 to 2022. The results reveal that the employment-to-population ratio, inflation rate, urbanization, and age dependency ratio have positive and statistically significant impacts on the female labor force participation rate. This research offers valuable insights for formulating policies to foster female empowerment and overcome the obstacles that hinder their economic participation.

Creating products and services that satisfy individual and community needs is impossible without raw materials. This study takes a novel approach by integrating the economic dynamics and raw material consumption indicators of the European Union (EU). The study uses different econometric methods to analyze the relationship between GDP (gross domestic product) and the EU’s raw material consumption (RMC) from 2014–2023. Among the results, the panel data analysis model shows that the resource productivity of the EU improved during the period under review, whereas the material intensity decreased significantly. These trends significantly contributed to the relative decoupling of material consumption from GDP in the last decade. The results of the K-means cluster analysis highlight the regional economic differences within the EU. According to the results of the correlation analysis, EU member countries differ significantly in the efficiency of raw material use. Nevertheless, five member countries are robustly vulnerable to large-scale raw material use. The divergence calculation results show that while some countries use raw materials extremely efficiently to produce GDP, others achieve low efficiency. This unique approach and the resulting findings provide a new perspective on the complex relationship between economic growth and raw material use in the EU.

This study examines the microeconomic determinants influencing remittance flows to Vietnam, considering factors such as gender (SEX), age (AGE), marital status (MS), income level (INC), educational level (EDU), financial status (FS), migration expenses (EXP), and foreign language proficiency (LAN). The study analyzes the impact of these factors on both the volume (REM_VL) and frequency of remittance flows (REM_FR), employing ordered logistic regression on survey data collected from Vietnamese migrants residing in Asia, Europe, the Americas, and Oceania. The estimations reveal that migrants’ income, age, educational level, and migration costs significantly positively influence remittance flows to Vietnam. Conversely, the financial status of migrants’ families in the home country negatively impacts these flows. Gender and migration costs primarily influence the frequency of remittance transfers, but they do not have a significant effect on the volume of remittances. Although foreign language proficiency was introduced as a novel variable of the models, it does not demonstrate any significant impact in this study. Furthermore, the survey data and regression estimates suggest that two primary motivations drive remittances to Vietnam: altruistic motives and implicit loan agreements. This research contributes to a deeper understanding of remittance e behavior, particularly in the context of Vietnam’s status as a major labor exporter. The findings provide valuable insights for policymakers and researchers seeking to optimize remittance flows and their impact on the Vietnamese economy. By understanding the complex interplay of factors influencing remittance behavior, policymakers can design effective strategies to support migrants and encourage increased remittance inflows, ultimately contributing to economic development and poverty reduction.