Impact of go global strategy on green growth in bri and non-bri economies: Evidence from a double machine learning approach
Wang, Yangjie Shinwari, Riazullah Saleem, Irfan Junjun, Z.
Wang, Yangjie
Shinwari, Riazullah
Saleem, Irfan
Junjun, Z.
Publication Date
2025-11
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(c) 2025 The Authors. This is an Open Access article distributed under the Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0/)
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2025-09-19
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Abstract
As a key stakeholder in global economic and environmental progress, China plays a pivotal role in advancing sustainability. This study examines China's Go Global (GG) strategy impact on green growth (GRG) across BRI and non-BRI economies from 2000 to 2023. The findings from double machine learning (DML) and traditional econometric methods indicate that the GG strategy significantly enhances GRG in BRI and non-BRI economies. These findings are further validated through the absence of endogeneity issues and robustness checks. Meanwhile, green initiatives like BRIGC, BRF, and BRI are instrumental in linking the GG strategy and GRG. Moreover, considering aggregate analysis and excluding global major shocks (i.e., the COVID-19 pandemic, the US-China trade war, and the global financial crisis) confirms that the GG strategy consistently promotes GRG, highlighting its resilience and effectiveness. Policymakers should integrate sustainable practices into infrastructure and transport, enhance biodiversity finance, and prioritize green energy and green innovation through expanded green financing to support green growth (SDG 8) across BRI and non-BRI countries.
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Citation
Wang Y, Shinwari R, Saleem I et al (2025) Impact of go global strategy on green growth in bri and non-bri economies: Evidence from a double machine learning approach. Journal of Environmental Management. 394: 127418.
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