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Institutional Quality and Economic Growth in the Energy Transition of MENA Countries

Author

Listed:
  • Abderraouf Mtiraoui

    (Doctoral School of Sousse, MOFID, University of Sousse, Tunisia)

  • Marwa Lazreg

    (University of Sousse, Sousse, Tunisia)

  • Leila Chemli

    (MOFID, University of Sousse, Tunisia)

Abstract

This paper investigates the energy transition in MENA region countries, emphasizing the pivotal role of institutional quality and its impact on economic growth. It explores the interactions between institutional quality, energy transition initiatives, and economic growth, aiming to understand how strong institutions can facilitate a successful transition. The empirical analysis employs a simultaneous equations model to identify institutional factors that can either support or hinder the energy transition and its influence on economic growth. The findings provide valuable insights for policymakers and economic stakeholders, underscoring the critical importance of robust institutions in driving the energy transition process and stimulating economic growth in the MENA region from 2000 to 2022.

Suggested Citation

  • Abderraouf Mtiraoui & Marwa Lazreg & Leila Chemli, 2024. "Institutional Quality and Economic Growth in the Energy Transition of MENA Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 14(6), pages 605-613, November.
    • Handle: RePEc:eco:journ2:2024-06-59
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    More about this item

    Keywords

    Institutional Quality; Economic Growth; Energy Transition and Simultaneous Equation Model;
    All these keywords.

    JEL classification:

    • B55 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Social Economics
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • A19 - General Economics and Teaching - - General Economics - - - Other
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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