How does economic complexity affect natural resource extraction in resource rich countries?
Ul-Durar, Shajara, Arshed, Noman, Anwar, Awais, Sharif, Arshian and Liu, Wei (2023) How does economic complexity affect natural resource extraction in resource rich countries? Resources Policy, 86. p. 104214. ISSN 03014207
Item Type: | Article |
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Abstract
Several studies debate whether natural resources benefit or hurt an economy. In natural resource-rich economies researchers cannot conclude it. This study examines the relationship between natural resource rent, economic complexity, clean technology, and natural resource productivity capacity in 20 resource-rich economies from 2000 to 2021. Coal, oil, minerals, natural gases, and forest rents are disaggregated in the study. The economic complexity curvilinear function illustrates the inverse U-shaped relationship under the environmental Kuznets curve (EKC) or the U-shaped relationship under load capacity curve (LCC) between economic complexity and natural resources rent. This study hypothesizes that economic complexity increases resource extraction curvilinearly, changing resource rents which may have implications in the transition towards clean energy under COP27 to achieve SDGs. The study shows the marginal effects of economic complexity at different levels of complexity and resource extraction using quadratic and quantile functions. This study first examines resource extraction quantiles. Economic complexity raises forest, coal, and mineral rents at low resource extraction. Economic complexity lowers forest, gas, oil, coal, and mineral rents at high resource extraction. This study describes the curvilinear function. At the median resource extraction level, economic complexity has an inverted U-shaped effect on forest, mineral, and coal rents and a U-shaped effect on gas and oil rents. This implies that an increase in economic complexity can be targeted which may reduce reliance on forests, minerals, and coal while reducing reliance on gas and oil, government effort, green technology, and productive capacity needed to be pursued.
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More Information
Uncontrolled Keywords: Quadratic function Quantile ARDL regression Productive capacity index |
Depositing User: Shajara Ul-Durar |
Identifiers
Item ID: 17052 |
Identification Number: https://doi.org/10.1016/j.resourpol.2023.104214 |
ISSN: 03014207 |
URI: http://sure.sunderland.ac.uk/id/eprint/17052 |
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Catalogue record
Date Deposited: 23 Nov 2023 16:37 |
Last Modified: 23 Nov 2023 16:45 |
Author: | Shajara Ul-Durar |
Author: | Noman Arshed |
Author: | Awais Anwar |
Author: | Arshian Sharif |
Author: | Wei Liu |
University Divisions
Faculty of Business, Law and Tourism > Sunderland Business SchoolSubjects
Business and Management > Business and ManagementActions (login required)
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