Jean Damascene Mvunabandi

The economic impact of carbon emissions in Africa is gaining traction in the extant literature. This study adopted Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to concomitantly track data on carbon emissions versus economic growth in Africa from 2018 to 2022 providing evidence from a meta-analysis. Through database searches, 591 publications were identified. A machine learning algorithm called Latent Dirichlet Allocation (LDA) was used as a visualization technique for reporting trends in the eleven papers selected for the analysis. Identifying, evaluating, and summarizing the findings of all relevant individual studies conducted in Africa on the impact of economic growth on carbon emissions contributes to the existing body of knowledge. This study fills a critical gap by surveying the studies conducted in Africa in the last five years, implying that economic growth negatively and significantly triggers CO2 emissions in Africa. The debate on the economic impact of CO2 emissions in Africa, the most vulnerable continent to climate change, is elucidated. The findings tracked sources of data for carbon emissions in Africa. The results showed that although some studies reported a positive correlation (and some a negative correlation) between economic growth and carbon emissions, most studies concur that the economic impact of carbon emissions over a timeline can be explained by the Environmental Kuznets Curve (EKC) hypothesis. Therefore, there is a dire need for African countries to strengthen economic growth without deteriorating their environment or having ecological footprint. Future research must assess whether this trend on the economic impact of carbon emissions in Africa continues.

Acknowledgment
The authors express their appreciation to the Durban University of Technology for providing the resources to conduct this study.

Type of the article: Research Article

Audit committees are key in corporate reporting, ensuring credibility through internal controls, assurance processes, and risk management. This study examines the relationship between audit committee characteristics and Environmental, Social, and Governance reporting quality among the top 100 Johannesburg Stock Exchange-listed corporations. Using agency and legitimacy theories, the study analyzes how audit committees serve as mechanisms for lowering information asymmetries and attaining legitimacy through transparent Environmental, Social, and Governance reporting. It focuses on three audit committee attributes: independence, meeting frequency, and average age. Panel data regression models using Ernst & Young’s Excellence in Integrated Reporting Awards were used. Data were obtained from the Bloomberg database spanning five years (2017–2021). The results reveal a significant positive correlation between Environmental, Social, and Governance reporting quality and audit committee independence (p-value < 0.05), but no significant relationship for meeting frequency or average age (p < 0.05). The findings highlight the importance of internal assurance in enhancing Environmental, Social, and Governance reporting, addressing stakeholder concerns on sustainability and corporate responsibility. The study contributes to the governance literature by offering actionable insights for firm managers and evidence that stronger audit committee independence enhances governance structures. This study underscores the need for policies that improve Environmental, Social, and Governance reporting quality and suggests further exploration of qualitative audit committee attributes influencing Environmental, Social, and Governance disclosures. It added to the ongoing debate examining the effect of audit committee characteristics on Environmental, Social, and Governance reporting quality in South Africa’s context.

Acknowledgment
Gratitude is extended to the anonymous referees for their helpful and thoughtful suggestions, recommendations, and constructive comments, by which the paper was substantially improved. Moreover, the University of KwaZulu Natal is acknowledged for providing excellent research support and facilities. Notably, the article has never been published previously. The paper was extracted from Ruth Mutsa Ruziwa’s Masters dissertation, which was submitted to the University of KwaZulu Natal, with first authorship of this article attributed to the same.

Type of the article: Research Article

Abstract
Electricity energy consumption plays a significant role in both local and international financial development. However, an imbalance between demand and supply of energy, especially electricity, impedes financial performance on both national and local levels. The purpose of this study is to investigate the dynamic impact of load shedding on financial performance in KwaZulu-Natal. A panel Autoregressive Distributed Lag (ARDL) model, the Toda-Yamamoto Granger causality test, and Error Correction Model (ECM) approaches were applied to a data sample from seven district municipalities for a period from 2016 to 2022. The results reveal an inverse long-term relationship between load shedding and municipal financial performance. Additionally, the Toda-Yamamoto causality analysis indicates a short-run bidirectional causality between load shedding and financial performance. This implies that a high level of electricity cuts leads to poor financial performance. Based on these findings, the study recommends that the government and policymakers implement strategies to improve electricity generation and distribution, and foster a more competitive energy market by allowing the entry of multiple electricity producers beyond Eskom. Furthermore, it advocates for increased investment in alternative energy sources such as solar, wind, and biogas as a means to mitigate load shedding and its adverse effects.

Type of the article: Research Article

Abstract
This study aims to examine the impact of blue accounting disclosures on the corporate environmental performance of 14 marine-sensitive companies operating in shipping, logistics, fishing, oil, and gas listed on the Johannesburg Stock Exchange (JSE). The study covered five years from 2019 to 2023. Data on environmental performance were collected and measured using Bloomberg environmental scores. Blue accounting disclosures were scored using a 5-point Likert scale. Various statistical and econometric techniques were employed, including descriptive statistics, correlation analysis, panel data analysis, and pooled ordinary least squares regression analysis. The findings show a significant positive correlation between environmental performance and firm size (coefficient: 16.07; p-value: 0.00), adherence to environmental guidelines (coefficient: 7.48; p-value: 0.02), and reporting costs (coefficient: 6.35; p-value: 0.01). Conversely, environmental obligations (coefficient: –3.92; p-value: 0.02) and firm age (coefficient: –0.18; p-value: 0.00) negatively correlated with environmental performance. The study recommends that marine-sensitive companies adopt blue accounting sustainability guidelines, like the Global Reporting Initiative (GRI), and that policymakers develop and enforce a blue accounting framework to promote sustainable marine practices. This study presents a novel model that integrates blue accounting disclosures. Through empirical and theoretical contributions, this study provided managerial, practical, policy, and implications for the quality of blue accounting disclosures, interventions, and policies to strengthen national and global sustainability goals. It added voice to the United Nations Sustainable Development Goals, specifically SDG 6 and SDG 14. This study also provided a robust research agenda for future research.

Type of the article: Research Article

Abstract
The connection between bad debts and bank profitability is vital for ensuring financial stability. However, while lending is a key source of banks’ revenue, rising bad debts can weaken their financial health, limit new credit issuance, and increase systemic risk. Therefore, understanding how bank-specific factors drive bad debts and affect profitability is crucial, particularly in distinguishing their impact on large and medium-sized banks. The purpose of this study is to assess the impact of bank-specific bad debts determinants on the profitability of South African banks. To achieve this objective, the study employs a Panel Autoregressive Distributed Lag (PARDL) model and an Error Correction Model (ECM) using bank data spanning the period from 2013 to 2023. The sample selection was informed by the data availability. The findings indicate that both the loan-to-deposit ratio and the capital adequacy ratio exert a positive impact on bank profitability, with large banks benefiting from stronger capital positions. The results further indicated that rising non-performing loan ratios correspond with decreased profitability in banks, particularly within medium-sized banks with limited risk absorption capacity. This research contributes to banking literature by offering a comparative perspective on the linkage between loans and both large and medium-sized banks in South Africa. The study suggests that, to mitigate potential defaults, medium-sized banks should exercise caution when issuing loans.