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Energy Efficiency and Economic Growth in Nigeria: A Long-Run Perspective

Author

Listed:
  • Jamiu Ibrahim Aminu

    (Faculty of Arts &Social Sciences, Gombe State University)

  • Mohammed Shamwil

    (Department of Economics & Development Studies, Federal University of Kashere, Gombe)

  • Ibrahim Abdullahi

    (Baze University, Abuja)

Abstract

This study investigates the relationship between energy efficiency and economic growth in Nigeria using time series data from 1980 to 2023 and the Stochastic Frontier Analysis framework. Results reveal that Nigeria?s energy demand is both price-elastic and income-elastic, indicating that changes in energy prices and income significantly influence consumption. Labour and capital act as substitutes for energy, while technological innovation boosts productivity but increases energy demand. The estimated average technical efficiency is relatively high at 95%, though marked by volatility and structural disparities across sectors. These findings highlight the critical role of policy consistency, reliable energy supply, and targeted investment in modern technologies to enhance efficiency and align Nigeria?s growth with sustainable development goals.

Suggested Citation

  • Jamiu Ibrahim Aminu & Mohammed Shamwil & Ibrahim Abdullahi, 0000. "Energy Efficiency and Economic Growth in Nigeria: A Long-Run Perspective," Proceedings of Economics and Finance Conferences 15016577, International Institute of Social and Economic Sciences.
    • Handle: RePEc:sek:iefpro:15016577
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    References listed on IDEAS

    as
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    Keywords

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    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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