Energy consumption (ECON) in BRICS countries is fueled by fossil fuels, mainly coal. Increased environmental degradation (ED) in BRICS countries is mostly driven by coal consumption. This study utilizes quantile regression for the analysis, enabling the development of targeted energy reorganization and emission reduction policies in BRICS countries. This study uses data spanning from 1990 to 2022 to explore the impact of ECON on ED. Additionally, technological innovation was used to create a moderating role in the nexus between ECON and ED. The model focuses on CO₂ emissions and the ecological footprint across ten BRICS countries. Among the nations included in the panel, the results indicate a significant dependence on cross-sectional factors. The study shows that ECON has a detrimental impact on ED across all quantiles. However, technological innovation reduces ED. In terms of a moderating role, technological innovation mitigates the negative influence of ECON on ED. Therefore, it is necessary to implement distinct policies in order to accomplish carbon emission reduction goals in various countries.

This study examines the short- and long-term effects of multiple quantiles of forward exchange rate premiums (FERPs) and COVID-19 cases on the quantiles of stock market returns (SMRs). We extend the Quantile Autoregressive Distributive Lag (QARDL) model, and the Multiple Threshold Non-linear Autoregressive Distributive Lag (NARDL) model propose a new Multiple Threshold Quantile Autoregressive Distributive Lag (MT-QARDL) approach. Unlike MT-NARDL, QARDL, and NARDL, the MT-QARDL model, which integrates the MT-NARDL model and the quantile regression methodology, captures both short- and long-term locational and sign-based asymmetries. For instance, at lower quantiles for Indian and Sri Lankan SMRs, bearish FERP exerts a positive influence, while bullish FERP has a negative effect during COVID-19. Conversely, bullish FERP negatively affects lower quantiles of SMRs of Bangladesh, India, and Sri Lanka, whereas bearish FERP either yields an opposite effect or remain statistically insignificant during COVID-19. The findings underscore long-term sign-based asymmetries due to the differential bearish and bullish FERP impact during COVID-19. However, in the long term, location-based asymmetries also existed as bullish FERP negative influence the SMRs of India, Bangladesh and Sri Lanka at higher quantiles but SMRs at lower quantiles insignificantly respond to the bullish FERP fluctuations during COVID-19.

The availability of efficient and sufficient energy infrastructure has a vital role in driving economic growth and development. In view of this, it is essential to ensure more investment in energy infrastructure. This study investigates the impact of public–private partnership (PPP) investments in the energy sector on poverty and unemployment rates in BRICS countries over a 24-year period. Employing the CS-ARDL model and validating the results using FMOLS, the analysis reveals that PPP investments in energy significantly reduce both poverty and unemployment in the long run. Furthermore, control variables such as foreign direct investment, control of corruption, and gross fixed capital formation also contribute to reducing poverty and unemployment. These findings remain robust across model specifications. The study provides important policy insights, suggesting that enhancing PPP investments in energy, alongside improved governance and strategic public spending can yield significant socio-economic benefits by reducing poverty and unemployment. This research contributes to the literature by offering empirical evidence on the socio-economic benefits of energy-focused PPPs.

It is necessary to ensure the thorough transition of energy dependency from fossil fuels to renewable energy as it is the sustainable source of energy. In this view, the study aims to explore the impact of digital transformation (DTR) on renewable energy adoption (REA). The analysis was set on the dataset of middle east countries over the span of 1999–2023. For checking the relationship, the study mainly considers the CS-ARDL model and proceeds with FMOLS model for robustness analysis. The findings infer that DTR positively influence the REA. This can be explained as DTR ensures the smooth flow of energy, internet of things, and better management of energy production and consumption. All these factors pave the way towards the transition of renewable energy. In addition, the analysis discloses the positive effect of FDI inflow, government effectiveness, and economic growth whilst urbanization negatively influence the REA. This research is novel because it thoroughly examines how institutional technological and economic factors influence REA in the Middle East, an area where there are currently few studies of this kind. The study’s conclusions give decision-makers doable plans to boost the regions sustainable development objectives and hasten the adoption of renewable energy.