ABSTRACT The rapid expansion of the digital economy is driving transformation in economic and industrial landscapes worldwide, while its impact on environmental performance remains a matter of debate. Therefore, this study examines the relationship between digitalization and environmental performance in BRICS+ countries over the period 2000–2024, with a particular focus on the mediating role of industrial structure. Digitalization is measured using two distinct indicators: digital infrastructure (DINF) and digital connectivity (DCO). The empirical analysis employs a two‐way fixed‐effect model with Driscoll‐Kraay (DK) standard errors as the baseline estimator, while panel threshold estimation is used to examine nonlinear effects across different levels of industrial development. Furthermore, the Feasible Generalized Least Squares (FGLS) and Panel‐Corrected Standard Errors (PCSE) estimations are employed as robustness checks. The results indicate that DCO is positively and significantly associated with environmental performance, whereas DINF does not exhibit a significant effect. The mediation analysis further reveals that industrial structure partially mediates the relationship between DCO and environmental performance, whereas no significant mediating effect is observed for DINF. Environmental performance is a strongly associated with government effectiveness, although the estimated effect of government effectiveness varies across different estimation methods. Economic growth and urbanization are negatively associated with environmental performance, while renewable energy consumption is positively associated with emissions, suggesting the existence of transitional challenges in the deployment of renewable energy. In addition, the panel threshold analysis indicates that the effect of digitalization on the environmental performance varies across different stages of the industrial development, highlighting structural transformation as a key factor in unlocking the environmental benefits of digitalization. The empirical findings provide important policy implications for promoting environmentally responsible digital transformation across BRICS+ countries.
ABSTRACT This study examines the joint impact of climate change exposure and biodiversity risk on the operational performance of 643 US firms during 2007–2022, focusing on their dynamic productivity change over time. Results show that they can hinder firm performance, with the joint impact played as the main channel of effect. These results were robustly derived from the 2SLS approach after accounting for the endogeneity issue and they do hold under various tests in terms of alternative dependent variables, alternative independent variables, and entropy balancing. Our findings speak to policy debates across Australasia and Southeast Asia regarding climate and biodiversity risk disclosure, offering a timely benchmark on the joint climate–biodiversity risks on firm performance.
ABSTRACT Scholarly outputs are the final goods of a heterogeneous, multi‐stage, temporally extended production process. Austrian capital theory provides a way to analyse how artificial intelligence changes that process. This paper conceptualises large language models and related tools not as labour substitutes but as a portfolio of capital goods whose productive role depends on how researchers (as entrepreneurs) specify and integrate them into a plan. AI adoption deepens and rearranges the capital structure of research. Because complementarity is plan‐relative, the effects of AI are intrinsically heterogeneous across researchers and fields, concentrating benefits where AI fills “holes” in an existing workflow and where complementary human capital is strongest. The framework yields practical and institutional implications, including changes to coauthorship incentives, disruptions to writing quality as a screening signal and a coordination problem as evaluation and peer‐review institutions adjust to a newly capital‐deepened production process.
ABSTRACT This study examines how digital economy‐green finance coordination influences economic growth quality across 15 emerging markets during 2010–2023. Coordination is measured through a coupling coordination degree integrating digital economy (five indicators from ITU, World Bank, UN) and green finance (five indicators from CBI, IRENA, World Bank, CCPI) subsystems. Growth quality is operationalized as an entropy‐weighted composite of 14 indicators across five dimensions, using exclusively open‐access data from 10 international databases. A coupling coordination model is employed to quantify the interactive harmony between digital economy and green finance systems, instrumental variable estimation (geographic latitude‐time interaction, F = 48.73) to address endogeneity, and bootstrap mediation analysis (1000 iterations) to identify transmission mechanisms. The results show that coordination significantly enhances growth quality ( β = 0.496, p < 0.01). The coupling coordination degree increased from 0.348 to 0.627 (80.2% improvement). Technological innovation (28.5%) and environmental improvement (26.8%) serve as primary transmission channels. Effects vary up to 3.3‐fold across income levels, infrastructure configurations, and policy environments. Results remain robust across 10 sensitivity specifications. However, manual data extraction may introduce measurement errors, and the sample ends at 2023; future research should employ enterprise‐level datasets and dynamic panel models. The findings support differentiated digital‐green development strategies: deep integration for high‐income economies, infrastructure development for middle‐income countries, and basic investment prioritization for low‐income contexts. This study provides the first cross‐country comparative analysis of digital economy‐green finance coupling coordination effects on growth quality in emerging markets, establishing a replicable paradigm using 10 freely accessible databases.
ABSTRACT As the core platform for global economic governance, the green transformation of the G‐20 countries is of vital importance to global sustainable development. This study, based on panel data from 1990 to 2023 and using a second‐generation econometric method, examines the impact of five factors—digitalization, fintech, trade openness, industrial growth, and per capita income—on the sustainability of natural resources. The findings are as follows: (1) Digitalization intensifies resource dependence, resulting in a “digital rebound effect”, with the transmission channel being the stimulation of consumer demand; (2) Fintech has the potential for “resource conservation” but the effect varies by country, with the transmission channel being green investment promotion; (3) Trade openness and industrial growth inhibit resource rents, verifying the environmental Kuznets curve from the resource perspective; (4) The interaction between digitalization and fintech, and between digitalization and trade openness generates a “doubled rebound effect”; (5) The impact of each factor varies systematically between developed and developing countries, as well as between emerging markets and non‐emerging markets. It is recommended that the G‐20 implement a comprehensive strategy integrating green digitalization, sustainable fintech, and clean industrial upgrading.
