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How does Digital Technology Influence Natural Resource Use: A Global Perspective

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  • Tomiwa Sunday Adebayo

    (Near East University
    University of Economics and Human Sciences
    State University of Economics (UNEC)
    Tashkent State University of Economics)

  • Victoria Olushola Olanrewaju

    (European University of Lefke)

  • Oktay Özkan

    (Tokat Gaziosmanpasa University)

  • Sajid Ali

    (Bahauddin Zakariya University)

Abstract

The integration of digital technology has become a critical determinant in reshaping the dynamics of natural resource rent on a global scale. This study examines the intricate relationship between digital technology and its impact on the economic rent derived from natural resource utilization and extraction within the framework of the global economy. Utilizing data spanning from 1990 to 2021, this research employs wavelet quantile-on-quantile regression to capture the complex interdependencies across various quantiles and periods. To the best of the authors' knowledge, this study represents the inaugural empirical investigation into this specific interrelationship, thereby addressing a significant gap in the existing literature. The findings reveal that digital technology, encompassing internet usage and mobile cellular subscriptions, negatively influences total natural resource rent. Moreover, digital technology reduces disaggregated natural resource rents, spanning oil, coal, natural gas, minerals, and forests. These results, corroborated by the findings from wavelet quantile regression, underline the need for global policymakers to prioritize initiatives to foster sustainable digitalization practices. This entails advocating for developing and adopting digital technologies that prioritize resource efficiency and conservation. Graphical Abstract

Suggested Citation

  • Tomiwa Sunday Adebayo & Victoria Olushola Olanrewaju & Oktay Özkan & Sajid Ali, 2025. "How does Digital Technology Influence Natural Resource Use: A Global Perspective," Computational Economics, Springer;Society for Computational Economics, vol. 66(4), pages 3567-3589, October.
    • Handle: RePEc:kap:compec:v:66:y:2025:i:4:d:10.1007_s10614-024-10800-4
    DOI: 10.1007/s10614-024-10800-4
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