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Geopolitical risk, green finance and natural resources: A novel analysis of China's national level data

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  • Li, Rongnan
  • Liu, Zhuang
  • Li, Shun
  • Geng, Jiao
  • Shi, Guanqun
  • Gu, Xiao

Abstract

Extensive literature analyzes the natural resources---economic growth--- environmental stability nexus; however, the role of green finance (GF) and geopolitical risk in the current scenario is missing. Thus, this research wants to evaluate the role of geopolitical risk (GPR), green finance, and natural resources in China's economic growth from 1991 to 2021. The research also included trade as a controlling variable in the study. Time series methods, ADF unit root test, Johansen Cointegration, and simple quantile regression are leveraged to analyze the data. The unit root test results reveal that data is static at level (1) and cointegration exists among variables. The outcomes from the QR analysis specify that GPR has a noteworthy and positive influence on economic growth at the median and upper quantiles. Additionally, both green finance and trade positively and significantly impact economic expansion across all quantiles. On the other hand, the results suggest a negative relationship between NRR and economic expansion, which supports the concept of the resource curse hypothesis. Moreover, the Granger causality test reveals a bidirectional causal connection between GDP and its explanatory variables. To ensure the robustness of these findings, a parametric approach was employed for a thorough analysis, which yielded similar results to the quantile regression estimates. Based on the established outcomes, this study offers meaningful policy implications for policymakers and researchers in promoting green finance, sustainable management of natural resources, and effectively addressing geopolitical risks that may affect economic growth.

Suggested Citation

  • Li, Rongnan & Liu, Zhuang & Li, Shun & Geng, Jiao & Shi, Guanqun & Gu, Xiao, 2023. "Geopolitical risk, green finance and natural resources: A novel analysis of China's national level data," Resources Policy, Elsevier, vol. 86(PB).
    • Handle: RePEc:eee:jrpoli:v:86:y:2023:i:pb:s0301420723009327
    DOI: 10.1016/j.resourpol.2023.104221
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