Green finance and foreign investment: catalysts for sustainable prosperity in emerging economies

Emerging economies grapple with the simultaneous challenge of fostering economic development and ensuring environmental sustainability, necessitating research that identifies key drivers of sustainable prosperity (SP). This study aims to analyze the heterogeneous impact and causal relationships of trade openness, population growth, environmental regulatory stringency, green patents, foreign investment, and green finance on SP in emerging economies. By examining these factors across 12 nations from 1990 to 2022, it seeks to uncover how financial and regulatory mechanisms can drive sustainable development. Using advanced econometric techniques, including MMQR, robustness tests (AMG, CCEMG, FE), and Granger-causality analysis, the findings reveal significant heterogeneity and causal relationships. MMQR highlights the critical roles of green finance, foreign investment, and green patents, with population growth showing varying effects across quantiles. Robustness tests corroborate these findings, while Granger-causality confirms bidirectional relationships between SP and both green finance and population growth. This research is novel in its application of a comprehensive methodological framework to explore these dynamics in emerging economies. The results offer practical recommendations for policymakers, highlighting the necessity for focused green finance initiatives, flexible regulatory approaches, and investment-friendly policies that correspond with long-term sustainability objectives. The paper identifies critical areas for future research, including the incorporation of machine learning techniques to enhance predictive models and the examination of institutional quality’s influence on sustainability results. These findings enhance the overarching dialogue on fulfilling SDGs and COP commitments, providing a framework for reconciling economic advancement with environmental conservation.

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Publication Details

Journal
Frontiers in Environmental Science
Published
2025-04-23
DOI
https://doi.org/10.3389/fenvs.2025.1561838
Citations
4
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
12.52
Controls
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article

Green finance and foreign investment: catalysts for sustainable prosperity in emerging economies

Honglin Wang
4 citations
Frontiers in Environmental Science
Energy, Environment, Economic Growth
12.52
article

Green finance and foreign investment: catalysts for sustainable prosperity in emerging economies

Honglin Wang
article en
4 citations

Abstract

Emerging economies grapple with the simultaneous challenge of fostering economic development and ensuring environmental sustainability, necessitating research that identifies key drivers of sustainable prosperity (SP). This study aims to analyze the heterogeneous impact and causal relationships of trade openness, population growth, environmental regulatory stringency, green patents, foreign investment, and green finance on SP in emerging economies. By examining these factors across 12 nations from 1990 to 2022, it seeks to uncover how financial and regulatory mechanisms can drive sustainable development. Using advanced econometric techniques, including MMQR, robustness tests (AMG, CCEMG, FE), and Granger-causality analysis, the findings reveal significant heterogeneity and causal relationships. MMQR highlights the critical roles of green finance, foreign investment, and green patents, with population growth showing varying effects across quantiles. Robustness tests corroborate these findings, while Granger-causality confirms bidirectional relationships between SP and both green finance and population growth. This research is novel in its application of a comprehensive methodological framework to explore these dynamics in emerging economies. The results offer practical recommendations for policymakers, highlighting the necessity for focused green finance initiatives, flexible regulatory approaches, and investment-friendly policies that correspond with long-term sustainability objectives. The paper identifies critical areas for future research, including the incorporation of machine learning techniques to enhance predictive models and the examination of institutional quality’s influence on sustainability results. These findings enhance the overarching dialogue on fulfilling SDGs and COP commitments, providing a framework for reconciling economic advancement with environmental conservation.

Frontiers in Environmental ScienceVol. 13
Renmin University of China (CN)
Openalex Percentile: Top 2%
Energy, Environment, Economic Growth
12.52
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