Green growth exhibits an immense potential to transform economies and safeguard the planet as it creates a symbiotic relationship between economic progress and environmental protection. This study examines the impact of green innovation, renewable energy consumption, and institutional quality on green growth in African countries, controlling for GDP per capita, trade openness, foreign direct investment (FDI), population, and natural resource rent. The short- and long-run relationships are investigated using pooled mean group (PMG), mean group (MG), and dynamic fixed effects (DFE) models with panel data for 49 African countries from 2000 to 2021. The findings reveal that green innovation, renewable energy consumption, institutional quality, GDP per capita, trade openness, and population growth have positive long-run effects on green growth. In contrast, FDI and natural resource depletion have adverse effects. In the short run, only institutional quality and GDP per capita positively affect green growth, while natural resource rent has a negative impact. Considering these findings, this study recommends that policymakers in Africa promote green innovation and adopt energy-efficient technologies, increase the use of renewable energy resources, and improve institutional quality to achieve green growth.

This study examines the interactions among economic growth, technological innovation, renewable energy consumption, and carbon emissions in Africa using advanced econometric methods. Panel data analysis reveals both symmetric and asymmetric impacts on carbon emissions, showing how economic and technological variables contribute to environmental outcomes. The augmented mean group (AMG) and common correlated effects mean group (CCEMG) estimators address cross-sectional dependence and heterogeneity, ensuring robust results. Findings indicate that positive economic growth increases emissions, while economic downturns significantly reduce emissions. The study underscores the need for strategic policies that leverage technological innovations and renewable energy to promote sustainable development in African economies, balancing economic growth with environmental protection.

Carbon emissions are a global issue that has drawn policymakers' and scholars' attention. This study delved into examining the effect of globalization and financial development on carbon emissions within 52 African economies from 1997 to 2002. Energy consumption and population size were also considered controlling factors influencing carbon emissions. The study employs a two-step system-generalized method of moment (GMM) to analyze the effects, using the KOF Globalization Index and the IMF's Financial Development Index. The results indicate that carbon emissions increase with economic growth, energy consumption, and population size. Moreover, this study supports the Environmental Kuznets Curve (EKC) hypothesis. The study also reveals that globalization and its sub-indices, financial development, and financial institutions exhibit a linearly increasing role in carbon emissions. However, financial markets have a negligible effect. Nonlinearly, the squared of globalization and its sub-indices of economic and social dimensions, squared financial development, and its sub-indices exhibit a negative impact, portraying an inverted U-shaped association with carbon emissions. Meanwhile, political globalization follows a U-shaped trend. Additionally, globalization, financial development, and their sub-indices moderate carbon emissions. The implications of these findings underscore the importance of sustainable practices, green financing, and collaborative partnerships for a more environmentally sustainable path.

This paper studies how artificial-intelligence (AI) disclosure in the Item 1A risk factors of S&P 500 10-K filings evolved between fiscal years 2015 and 2025. It asks three questions: when AI disclosure became common in Item 1A; whether firm characteristics explain which firms disclose and whether that power changes as disclosure spreads; and whether firms that write more AI text write less firm-specific AI language. The data are a panel of 5214 firm-years for the 501 firms in the S&P 500 as of April 2026, so the sample is subject to survivor bias; the coverage gap relative to the historical index is about 38% in 2015 and falls to 2% by 2025. AI mentions come from a hand-validated keyword dictionary, and a lexical distinctiveness score measures how far a firm’s AI wording departs from that of its peers in the same year; the score captures wording, not informational content or quality. Three results follow. First, the share of firms disclosing AI in Item 1A rises from 0.7% to 77.6%, with the largest jump in the first filing cycle after the November 2022 release of ChatGPT. Second, the power of firm characteristics to discriminate disclosers falls as disclosure saturates: the disclosure logit’s pseudo-R² drops from 0.24 to 0.03 and the area under the ROC curve from 0.86 to 0.61. Third, among disclosing firm-years, more AI text is associated with lower lexical distinctiveness. These associations are descriptive; this paper does not test causal mechanisms.

This study examines the effects of the COVID-19 pandemic on the Türkiye stock market between March 14, 2020, and April 29, 2022, using the Quantile Autoregressive Distributed Lag (QARDL) model. The research investigates the relationship between the BIST100 index and selected economic indicators across quantiles ranging from 0.05 to 0.95. These indicators include daily new COVID-19 cases, the dollar exchange rate (FX), Brent crude oil prices (OIL), and credit default swap (CDS) rates. Findings indicate that an increase in COVID-19 cases has a negative impact on the stock market across various quantiles. While the dollar exchange rate generally shows a positive relationship with the BIST100 index, Brent crude oil prices, and CDS rates exhibit a negative impact. These results highlight the complex effects of both internal and external factors on the Türkiye stock market, providing significant insights for policymakers and future research.

To address ecological degradation in Sub-Saharan Africa, enhancing ecological sustainability requires combining FinTech-enabling digital readiness with fiscal capacity. Although existing African research did examine digitalization, financial development, and environmental sustainability, it lacks a comprehensive framework that explains in particular how FinTech-enabling digital readiness interacts with domestic fiscal capacity, which in this context illustrates a significant gap in regional green-development strategies. This study aims to assess ecological sustainability across 31 Sub-Saharan African countries from 1990 to 2024 using an unbalanced panel of 766 country-year observations, employing Method of Moments Quantile Regression within an extended STIRPAT framework that integrates fiscal capacity and its interaction with FinTech-enabling digital readiness. Internet usage is employed as a proxy for the digital-readiness dimension of FinTech, while tax revenue as a share of GDP represents fiscal capacity. The empirical results show heterogeneous effects across the conditional distribution of ecological sustainability. FinTech-enabling digital readiness shows a positive effect on ecological sustainability, indicating that greater digital connectivity is associated with improved ecological performance across Sub-Saharan African economies. Fiscal capacity in turn exhibits a negative direct effect on ecological sustainability. However, its interaction with FinTech-enabling digital readiness is positive and statistically significant, showing that stronger domestic revenue capacity enhances the ecological contribution of digital connectivity. In the model we also find that trade openness and population density reduce ecological sustainability, while economic development improves it, and the main findings remain robust under Driscoll–Kraay, Fully Modified Ordinary Least Squares, Dynamic Ordinary Least Squares, and Canonical Cointegrating Regression estimations. Moreover, the findings indicate that the environmental benefits associated with FinTech-enabling digital readiness become stronger when digital connectivity is supported by greater domestic fiscal capacity. As per our results, we suggest strengthening the complementarities between digital connectivity and domestic revenue mobilization and directing fiscal resources toward green-development priorities to translate digital readiness into stronger state capacity for ecological sustainability.