Investigating economic growth and natural resource dependence: An asymmetric approach in developed and developing economies

Syed Abdul Rehman Khan, Pablo Ponce, Zhang Yu, Katerine Ponce

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Economic growth is one of the primary macroeconomic aggregates that governments seek to achieve due to the positive externalities it generates in a nation. Natural resources are one of those factors that can be seen as a blessing or a curse in determining economic growth. Nowadays, it has been shown that countries can base their economic growth on factors other than capital formation and the intensive use of the labour force. Therefore, this research aims to examine the causal link between economic growth and capital formation, the labour force, renewable energy and renewable energy, the technological innovation at a global level and in groups of countries classified according to their level of income, developed and developing countries. Next, second-generation econometric techniques have been used that control the cross-sectional dependence among the countries examined. Then, the long-term coefficients are examined using the Method of Moments Quantile Regression (MMQR). The results find that the regressor variables are positively associated with economic growth, showing heterogeneity in the various quantiles examined. In addition, there is variation in results when examining economic growth by groups of countries, which shows the intensive use of factors. The results obtained reveal several policy implications aimed at sustainable growth in the era of post-COVI-19.

Original languageEnglish
Article number102672
JournalResources Policy
Volume77
DOIs
StatePublished - Aug 2022

Bibliographical note

Funding Information:
This research was supported by the Beijing Key Laboratory of Urban Spatial Information Engineering (No. 20210218 ).

Publisher Copyright:
© 2022 Elsevier Ltd

Keywords

  • Dependence on natural resources
  • Economic growth
  • Natural resources
  • Quantile regression
  • Technological innovation

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