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Natural resources led financing of investment: A prospect of China's provincial data

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  • Zhang, Cong
  • Teng, Wei

Abstract

In the existing literature, very limited attention has been paid to exploring the factors influencing investment in the country. To bridge the gap from an emerging economy's perspective, this study investigated China's provincial data over the period 1995–2017. This study examines the influence of natural resources on the country's financial investment while considering the role of economic growth, technological innovation, and renewable energy. This study uses panel estimation approaches to validate the equilibrium in the long-run connection between the variables. Due to the non-normal distribution quality of data, the non-parametric approach (method of moment quantile regression) is used. The examined results asserted that economic growth and technological innovation are China's leading drivers of financial investment. However, natural resources and renewable energy are significantly reducing the level of investment across all quantiles. Hence, the phenomenon of natural resources-led financing investment is invalid in the case of China. The results are robust and consistent with the empirical findings of the panel dynamic ordinary least square and novel bootstrap quantile regression. Further, this study also discovers the two-way causality between these variables. Based on the results, this study recommends properly channeling natural resources to reduce corruption and mismanagement and increase investment in research and development. Also, technological innovation shall be enhanced, and the use of renewable energy consumption shall be encouraged to boost the country's overall investment level and sustainable development.

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  • Zhang, Cong & Teng, Wei, 2023. "Natural resources led financing of investment: A prospect of China's provincial data," Resources Policy, Elsevier, vol. 86(PB).
    • Handle: RePEc:eee:jrpoli:v:86:y:2023:i:pb:s0301420723008759
    DOI: 10.1016/j.resourpol.2023.104164
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