This paper explores the interconnected dynamics between governance, public debt, and domestic investment (also known as gross fixed capital formation (GFCF) in South Africa). It also highlights domestic investment as a key driver of economic growth, noting a consistent decline in investment since the country’s democratic transition in 1994. Moreover, this downward trend is exacerbated by excessive public debt, poor governance, and increased economic risks, discouraging domestic and foreign investments. The analysis incorporates two theoretical perspectives: endogenous growth theory, which stresses the significance of local capital investment and innovation, and institutional governance theory, which focuses on the role of governance in promoting economic development. The study reveals that poor governance, rising debt, and high economic risks have impeded GFCF and economic stability. By utilizing quantitative data from 1995 to 2023, the research concludes that reducing public debt, improving governance, and minimizing economic risk are critical to revitalizing domestic investment in South Africa. These findings suggest that policy reforms centered on good governance, effective debt management, and economic stabilization can stimulate investment, promote growth, and address the country’s economic challenges. This study offers insights into how governance and fiscal policies shape investment and capital formation in a developing nation, providing valuable guidance for policymakers and stakeholders working towards sustainable economic growth in South Africa.

In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pick up important patterns from the dataset. Random Forest was not much behind with an accuracy of 0.128119 and highest precision score of 0.118553 knit a great ability for handling relations in large dataset but with slightly lower recall in comparison with Neural Network. This ranked the Decision Tree model at number three with a 0.111792, Accuracy Score while its Recall score showed it can predict true positives better than Support Vector Machine (SVM), although it predicts more of the positives than it actually is a majority of the times. SVM ranked fourth, with accuracy of 0.095465 and F1-Score of 0.067861, the figure showing difficulty in classification of associated classes. Finally, the K-Neighbors model took the 6th place, with the predetermined accuracy of 0.065531 and the unsatisfactory results with the precision and recall indicating the problems of this algorithm in classification. We found out that Neural Networks and Random Forests are the best algorithms for this classification task, while K-Neighbors is far much inferior than the other classifiers.

This study investigates the impact of Foreign Direct Investments (FDIs) on wage dynamics in Slovakia and Slovenia, with a particular emphasis on gender-specific effects in post-Communist emerging markets. By analyzing wage outcomes for male and female workers separately, the research reveals potential disparities in FDIs-driven wage growth. Employing econometric techniques and longitudinal data, the study explores the nuanced relationship between FDIs, wage policies, and economic development over time. A temporal lag in FDIs analysis suggests that Slovakia and Slovenia have experienced differing impacts from past foreign capital flows. In Slovakia, significant correlations indicate persistent FDIs influence and a pronounced effect on gender wage disparities. In Slovenia, more moderate correlations and FDIs volatility suggest a less stable relationship between external investment and wage dynamics. The originality of this research lies in its comparative approach, examining two distinct post-Communist nations and identifying unique country-specific patterns and trends. This study contributes to a deeper understanding of FDI’s role in labor market management and its implications for gender equality in two European emerging economies.

This study examines the impact of parliamentary thresholds on the Indonesian political system through the lens of the Routine Policy Implementation Model and the Strategic Policy Implementation Model. The main objective is to evaluate the effectiveness of parliamentary thresholds in managing political fragmentation, assess their impact on stability and representation in the legislative system, and understand their implementation’s technical and strategic implications. Using a qualitative approach supported by interview studies and field observations, this research combines analysis of election data in the 2009, 2014, and 2019 elections with a qualitative assessment of policy changes and political dynamics. The Routine Policy Implementation Model focuses on the technical aspects of threshold implementation, including vote counting procedures and seat allocation efficiency. Meanwhile, the Strategic Policy Implementation Model examines the broader implications of these thresholds for political consolidation, government effectiveness, and the representation of minor parties. The results show that the parliamentary threshold has significantly reduced political fragmentation by consolidating the number of parties in Parliament, resulting in a legislative system that is cleaner and easier to administer. However, this consolidation has also marginalized small parties and limited political diversity. The novelty of this study lies in its comprehensive analysis of how parliamentary thresholds affect administrative efficiency and strategic political stability in Indonesia, compared to democratic countries in transition, such as Slovenia and Montenegro. In conclusion, although parliamentary thresholds have increased political stability and government effectiveness, they have also raised concerns about the reduced representation of small and regional parties. The study recommends maintaining balanced thresholds that ensure stability and diversity, implementing mechanisms to review thresholds periodically, and involving diverse stakeholders in adjusting policies to reflect evolving political dynamics. This approach will help balance the need for a stable legislative environment with broad representation.

This study investigates the impact of tourism and institutional quality on environmental preservation, utilizing principal component analysis to generate three composite indices of environmental sustainability for 134 countries from 2002 to 2020. The results reveal that environmental sustainability indices have generally improved in lower- and middle-income nations but have declined in certain high-income countries. The findings also underscore the critical role of institutional quality—particularly regulatory standards, government effectiveness, anti-corruption efforts, and adherence to legal frameworks—in promoting environmental sustainability. However, the study shows that both domestic and international tourism expenditures can have adverse effects on environmental sustainability. Notably, these negative effects are exacerbated in countries with well-developed institutions, which is an unexpected outcome. This highlights the need for careful, thoughtful policymaking to ensure that the tourism sector supports sustainable development, rather than undermining environmental objectives.

This study aims to scrutinize specific long-term sustainability industrial indicators in Thailand as a representative of an emerging economy. The study uses a Bloomberg database comprising all Thai listed companies on the Stock Exchange of Thailand from 2013 to 2023. The research employs a two-step Generalized Method of Moments (GMM) statistics to assess the enduring impact on industrial sustainability. These results provide consistent, significant and positive relationships between asset turnover and sales with all industrial sustainability. The results additionally reveal that some other factors may moderate industrial sustainability but reveal the GDP growth rate and institutional shareholders are less likely to be corporate sustainability to all indicators. The results provide insight into valuable guidance to management teams, financial statements’ users, investors and other stakeholders on designing effective operations and investment strategies to improve sustainability.