The worldwide move toward renewable energy indicates a fundamental change that is particularly important in the MENA region, which has abundant renewable resources and has depended on hydrocarbon economies. This study presents an empirical examination of key macroeconomic determinants—inflation, fiscal policy, and economic volatility—on renewable energy security in MENA countries from 2000 to 2023. Applying a Panel Autoregressive Distributed Lag (ARDL) model of 16 countries, we assess the short-run dynamic and long-run equilibrium relationships, where renewable energy security is measured using the share of renewable electricity in total generation. These results support the existence of a significant long-run cointegrating relationship. We find fiscal policy to have a positive effect on renewable energy security, while inflation and economic volatility have significant negative short- and long-term effects. The error-correction term of −0.421 signaled a relatively fast return to long-run equilibrium. We conclude that sound management of these macroeconomic variables—especially price stability and counter-cyclical fiscal policies—is an essential precondition for achieving renewable energy security in the MENA region. Our policy implications highlight the need to support stable investment inquiries led by coordinated monetary, fiscal, and energy policies aimed at creating the conditions for renewable energy security.

This paper examines bank failures during the subprime mortgage crisis, emphasizing sibling dynamics within multi-bank holding companies (MBHCs). While traditional risk indicators effectively predict failures for one bank holding companies (OBHCs), they exhibit limited explanatory power for MBHCs, where internal capital markets and interdependencies across affiliates shape risk outcomes. We extend the standard failure framework by incorporating group-level characteristics that capture sibling network structure and the distribution of risk across affiliates. Using pre-crisis data from 2006 to 2007, we show that group structure significantly influences failure risk. Larger sibling networks reduce individual bank failure risk through diversification, while greater size dispersion across affiliates increases vulnerability by constraining internal resource allocation. Beyond these aggregate effects, we introduce a weakest link approach that identifies the most distressed affiliate based on extreme tail risk in capitalization, asset quality, liquidity, earnings, and income volatility, capturing organizational fragility that aggregate measures miss. Concentrated vulnerabilities at a single affiliate significantly amplify failure risk throughout the holding company, even after controlling for traditional bank-level fundamentals and parent-level characteristics. These findings, derived from the 2007–2010 crisis, a severe stress test of holding company structures, identify organizational dynamics: resource competition among siblings and concentrated vulnerabilities at the weakest affiliate. Supervisory frameworks should explicitly account for within-group interdependencies rather than relying solely on individual bank metrics or aggregate indicators when monitoring bank holding company structures.

Emerging economies confront the dual challenge of accelerating digital transformation while simultaneously mitigating environmental degradation under conditions of institutional and governance heterogeneity. In this context, this study examines how artificial intelligence (AI) capability influences green innovation efficiency (GIE) in emerging Asian economies and investigates whether environmental, social, and governance (ESG) performance conditions this relationship. Using an unbalanced panel of 59,112 firm-year observations from 4926 publicly listed firms across 15 emerging Asian economies over the period 2011–2022, we employ a comprehensive panel-data econometric framework that accounts for unobserved heterogeneity, dynamic effects, endogeneity, and potential self-selection bias. The empirical results indicate that AI capability is positively and significantly associated with higher green innovation efficiency. More importantly, ESG performance strengthens this relationship, suggesting that robust governance frameworks enhance firms’ ability to translate digital intelligence into environmentally efficient innovation outcomes. These findings underscore that AI adoption alone is insufficient to generate sustainable value; rather, its environmental effectiveness depends critically on complementary governance structures that promote transparency, accountability, and responsible risk management. The results remain robust after correcting for endogeneity concerns, alternative model specifications, and extensive sensitivity and heterogeneity analyses. Overall, this study contributes to the literature on digital transformation and sustainability by providing large-scale, multi-country evidence that highlights the pivotal role of ESG in shaping the sustainability returns to AI adoption in emerging economies.

Many emerging economies seek to lower carbon intensity while remaining heavily dependent on fossil fuels. This paper examines how sustainable finance, eco-innovation, and the energy mix shape Tunisia’s low-carbon transition. We use quarterly data for 2000–2023 and an econometric environmental-impact model that links carbon intensity to green finance, innovation, renewable and fossil energy, openness, income, and demographic factors. The results show that sustainable finance consistently reduces carbon intensity across all emission states, with stronger effects when emissions are high. The energy mix is crucial: a larger share of renewable energy lowers carbon intensity, while higher fossil energy use increases it and reinforces fossil carbon lock-in. Eco-innovation has its strongest mitigation effects in high-intensity situations, suggesting delayed effects linked to limited absorptive capacity and technology diffusion. Openness and demographic pressure tend to raise emissions through scale and consumption channels. Overall, the findings depict a finance-anchored but energy-constrained transition. They indicate that Tunisia and similar MENA economies can accelerate decarbonization by scaling credible sustainable finance instruments, speeding up renewable deployment, and strengthening the innovation and governance framework that supports green investment, innovation policy, and energy sector reform in semi-industrialized economies.

Financial distress prediction models are widely used to support risk management. However, economic turbulence, such as the COVID-19 pandemic, can disrupt the relationships between financial indicators and distress, thus threatening the stability and accuracy of the models’ predictions. In this study, the stability of bankruptcy prediction models is examined on a large sample of small and medium-sized enterprises (SMEs) in Slovakia. Three periods are distinguished: the pre-pandemic years 2018–2019, the COVID-19 pandemic years 2020–2021, and the post-pandemic recovery years 2022–2023. Two approaches to model construction are compared: separate models are estimated for each period, and a single comprehensive model covering all three periods is constructed with a period-specific indicator among the predictors. Publicly available financial data and machine learning methods are employed, and model performance is evaluated using common classification metrics. Differences in performance are revealed, indicating whether period-specific models provide superior predictive accuracy or whether a universal model can adapt to changing economic conditions. The robustness, stability, predictive power, and practical applicability of both approaches are assessed, and the influence of economic fluctuations on accuracy is demonstrated. The findings provide guidance on selecting modelling strategies across different economic environments and offer recommendations for further developing and implementing predictive models in volatile financial conditions.

This study aims to analyze the effect of remittances on multidimensional poverty in Mexico by comparing them with other sources of household income, such as labor income and social spending from transfers, subsidies, and allocations. Furthermore, economic growth dynamism is incorporated as a control variable. A micro-panel with cross-sectional and temporal fixed effects covering the 32 federative entities from 2010 to 2024 is used for this purpose. The results reveal that, although remittances have a moderate alleviating effect on poverty, it is greater than the impact of social spending by state governments. In contrast, labor income is identified as the main factor in reducing multidimensional poverty. These findings underscore the importance of promoting the utilization of remittance flows through financial inclusion strategies to strengthen their contribution to sustained household well-being and consolidate them as a structural instrument against the persistent challenges of multidimensional poverty in Mexico.

This study aims to assess whether country-level conditions traditionally associated with fostering entrepreneurship (such as digitization, economic climate, and government policies) explain the extent to which R&D leads to new commercial opportunities for small and medium-sized enterprises. Using data from the Global Entrepreneurship Monitor’s National Expert Survey, this study applies factorial analysis of variance models to evaluate the single and interaction effects of multiple categorical variables on R&D transference. Three models are constructed to test the significance of country: entrepreneurship-supportive factors, entrepreneurs’ recommendations, and pandemic-related government actions. The results reveal that country location consistently and significantly explains variance in R&D transference. In contrast, traditional entrepreneurship-fostering factors are not found to be statistically significant. Pandemic-related government actions also fail to demonstrate measurable explanatory power on R&D transference. These findings suggest that broader national contexts, rather than specific entrepreneurship-supportive conditions, are more critical in shaping R&D outcomes. Policymakers should reconsider the assumption that general entrepreneurship support mechanisms automatically enhance R&D transference. Instead, targeted interventions may be more effective. Entrepreneurs and investors should evaluate national contexts beyond perceived support factors when pursuing R&D-based innovation. The study underscores the need for context-sensitive strategies in fostering innovation and challenges one-size-fits-all approaches to entrepreneurship policy.

This study investigates how eco-innovation, digitalization, and economic complexity drive the circular economy in African economies between 2000 and 2024. Using the Dumitrescu–Hurlin causality test with POLS, DKSE, and MMQR estimators, we identify determinants of CE growth under varying conditions of development. Our results show the strongest positive effect on CE is induced by digitalization, followed by eco-innovation and economic complexity. In addition, digitalization equally enhances CE at all quantiles, while for eco-innovation, its contribution towards CE growth is greater in low-performing CE countries. The evidence suggests that in the course of its circular transformation, Africa needs to embark on digital infrastructure, innovation capacity, and productive diversification. Accordingly, such regional strategies will be contributing to SDG 9 on industry and innovation, SDG 12 on responsible consumption, and to the African Union Agenda 2063 for sustainable growth.

This paper investigates the determinants of economic growth in EU member states that joined the Union in 2004 and later, focusing on institutional quality, competitiveness, and the green transition. Three composite indices are constructed using principal component analysis (PCA) and incorporated into a panel ARDL-PMG model, complemented by robustness checks with fixed-effects and system-GMM estimators. The results highlight competitiveness as the most robust driver of growth across specifications, while institutional quality emerges as an enabling factor, particularly under dynamic specifications that account for endogeneity. The green transition shows significant long-run benefits, although its short-run effects are weaker, reflecting the gradual payoff of environmental investments. Policy implications emphasize the importance of strengthening institutional frameworks, fostering innovation and productivity, and sustaining commitments to the green transition as pillars of sustainable convergence. The findings enrich the literature on EU integration and provide evidence-based insights for aligning cohesion policy and the European Green Deal with growth objectives.

This article examines how the volatile oil price affected Saudi Arabia’s and the other GCC countries’ fiscal policy dynamics from 2000 and 2024. The region’s fiscal systems are vulnerable to external shocks due to their substantial reliance on petroleum profits, even with ongoing efforts to diversify. The dynamic links between government spending, budget balances and oil prices are examined using a panel vector Autoregression (PVAR) model. We also estimate different fiscal reaction functions for Saudi Arabia and several of its neighbors with somewhat more diversified income systems, like Kuwait and the United Arab Emirates. This study’s primary contribution is its direct comparative analysis of GCC fiscal responses using a long panel (2000–2024) that encompasses major oil price cycles, and the application of a dynamic PVAR framework to quantify the persistence and heterogeneity of these effects across countries. The data shows that different countries have different fiscal responses. For example, Saudi Arabia reacts to oil shocks more slowly than other nations with more diverse revenue sources, who have better consolidation mechanisms. These results highlight the necessity of strong fiscal frameworks that build resilience to fluctuations in commodity prices and offer insightful guidance to policymakers seeking sustainable fiscal management in countries that rely heavily on natural resources.