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Natural Resource Endowments and Growth Dynamics in Africa: Evidence from Panel Cointegrating Regression

Author

Listed:
  • Ibrahim A. Adekunle

    (Babcock University, Nigeria)

  • Olukayode E. Maku

    (Olabisi Onabanjo University, Nigeria)

  • Tolulope O. Williams

    (Olabisi Onabanjo University, Nigeria)

  • Judith Gbagidi

    (Africa PPP Advisory Services)

  • Emmanuel O. Ajike

    (Babcock University, Nigeria)

Abstract

Purpose With heterogeneous findings dominating the growth and natural resources relations, there is a need to explain the variances in Africa’s growth process as induced by robust measures of factor endowments. This study used a comprehensive set of data from the updated database of the World Bank to capture the heterogeneous dimensions of natural resource endowments on growth with a particular focus on establishing complementary evidence on the resource curse hypothesis in energy and environmental economics literature in Africa. These comprehensive data on oil rent, coal rent, and forest rent could provide new and insightful evidence on obscure relations on the subject matter. Design/methodology/approach This paper considers the panel vector error correction (PVECM) procedure to explain changes in economic growth outcomes as induced by oil rent, coal rent and forest rent. The consideration of the (PVECM) was premised on the panel unit root process that returns series that were cointegrated at the first-order differentials. Findings The paper found positive relations between oil rent, coal rent and economic development in Africa. Forest rent, on the other hand, is inversely related to economic growth in Africa. Trade and human capital are positively related to economic growth in Africa, while population growth is negatively associated with economic growth in Africa. Research limitations/implications Short-run policies should be tailored toward the stability of fiscal expenditure such that the objective of fiscal policy, which is to maintain the condition of full employment, economic stability, and stabilise the rate of growth, can be optimised and sustained. By this, the resource curse will be averted, and productive capacity will increase, leading to sustainable growth and development in Africa, where conditions for growth and development remains inadequately met. Originality/value The originality of this paper can be viewed from the strength of its arguments and methods adopted to address the questions raised in this paper. This study further illuminated age-long obscure relations in the literature of natural resource endowment and economic growth by taking a disaggregated approach to the component-by-component analysis of natural resources factors (the oil rent, coal rent and forest rent) and their corresponding influence on economic growth in Africa. This pattern remains underexplored mainly in previous literature on the subject. Many African countries are blessed with an abundance of these different natural resources in varying proportions. The misuse and mismanagement of these resources along various dimensions have been the core of the inclination toward the resource curse hypothesis in Africa. Knowing how growth conditions respond to changes in the depth of forest resources, oil resources and coal resources could be a useful pointer in Africa's overall use and management. This study contributed to the literature on natural resource-induced growth dynamics by offering a generalisable conclusion as to why natural resource-abundance economies are prone to poor economic performance. This study further asks if mineral deposits are a source or reflection of illgrowth and underdevelopment in African countries.

Suggested Citation

  • Ibrahim A. Adekunle & Olukayode E. Maku & Tolulope O. Williams & Judith Gbagidi & Emmanuel O. Ajike, 2023. "Natural Resource Endowments and Growth Dynamics in Africa: Evidence from Panel Cointegrating Regression," Working Papers 23/015, European Xtramile Centre of African Studies (EXCAS).
  • Handle: RePEc:exs:wpaper:23/015
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    References listed on IDEAS

    as
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    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • O44 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth

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