This study examines the current state of sustainable finance and proposes a strategic roadmap for its advancement in policy and practice, emphasizing the integration of sustainability principles into financial systems to address global environmental and social challenges. Using an integrative literature review of 684 scholarly articles—combining bibliometric analysis with manual review—the research identifies six critical themes and highlights major barriers such as regulatory ambiguity, lack of standardized metrics, and limited data availability. It offers targeted recommendations for policymakers, financial institutions, and stakeholders to overcome these challenges. The study provides a novel methodological contribution by merging bibliometric and qualitative insights, and outlines practical strategies to enhance regulatory frameworks, encourage innovation in sustainable finance, and promote emerging technologies like blockchain and artificial intelligence. Ultimately, it supports the integration of environmental, social, and governance (ESG) considerations into financial practices, fostering a more responsible and inclusive financial ecosystem.

This study explores the connections between renewable energy consumption (REC), non-renewable energy consumption (NREC), gross fixed capital formation (GFCF), the labor force (LF), and economic growth (GDP) in Renewable Energy Country Attractiveness Index (RECAI) countries for 1991–2016. We quantify the nexus between REC, NREC, and GDP while utilizing a production model framework and including the measures of labor and capital, for suggesting a phase-wise strategy to attain the sustainable development goals. We use robust methodologies including Lagrange Multiplier (LM) panel unit root tests with trend shifts, Westerlund cointegration test, LM bootstrap technique for cointegration with breaks, continuously updated fully modified (CUP-FM) and continuously updated bias-corrected (CUP-BC) estimators, Augmented Mean Group (AMG) approach, fully modified ordinary least squares, dynamic ordinary least squares, Canonical Cointegrating Regression (CCR), and panel causality test proposed by Canning & Pedroni. We compute non-parametric time-varying coefficients with fixed effects for seeing the impact of GFCF, LF, REC, and NREC on GDP. Our results press upon policymakers to shift toward clean energy and REC for attaining the environmental goals (SDGs 6, 7, 13, and 15) and the economic goals (SDGs 1, 2, 8, and 10). While this shift would help developed economies, which have already attained the economic goals, to progress on the front of environmental goals, it would enable developing countries to progress on both fronts in a balanced manner.

This research presents an in-depth investigation into the dynamic correlation between geopolitical conflicts and carbon markets utilizing the Time-Varying Parameter Vector Autoregression (TVP-VAR) technique. The analysis focuses on the interconnectedness between the Geopolitical Risk Index Daily (GPRD) and vital carbon pricing instruments, specifically the Intercontinental Exchange Endex European Union Allowance (ECEFDC), KraneShares California Carbon Allowance Strat ETF (KCCAK), Shanghai Environment and Energy Exchange China Emission Allowances Online Transactions (SAXCEA), and S&P Global Ex-Japan LargeMidCap Carbon Efficient Index (SPGJ). The daily fluctuations were traced from May 2021 to July 2023. The analysis is divided into short- and long-term connectedness, with particular emphasis on the impact of the Russia-Ukraine conflict on the GPRD's spillover on carbon markets. The short-term connectedness (1–5 days) between GPRD and ECEFDC shows variability, fluctuating between 10% and 40%. Conversely, long-term connectedness exhibited a significant increase during the conflict, peaking at approximately 34% by mid-2022. The analysis of the Total Dynamic Connectedness (TCI) between the GPRD and the KCCAK indicates comparable magnitudes, although with minor initial discrepancies. The short-term connectedness of GPRD and KCCAK decreases from its peak of approximately 10% to approximately 1%. Conversely, long-term connectedness varies between approximately 32% and 2% from May 2022 onwards. The long-term connectedness between GPRD and SAXCEA revealed variable patterns, peaking at around 18% at the beginning of the sample period and rapidly reducing to around 1% within two months. The analysis of the connectedness between GPRD and the SPG) identifies intense fluctuations in both TCI and long-term connectedness. After an initial increase and decrease, these patterns rebound and experience another increase. This research provides significant insights into the complex dynamics of geopolitical conflicts and carbon markets, particularly the impact of the Russia-Ukraine conflict on carbon market behavior.