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Government Educational Spending and Human Capital Development in ECOWAS Sub-Region: Implication For Sustainable Development

Author

Listed:
  • Oloke Emmanuel

    (University of Wales Trinity Saint David, UK)

  • Olanipekun Wahid Damilola

    (American International University, The Gambia)

  • Mabinuori Oladotun Toriola

    (Bells University of Technology, Nigeria)

  • Ojo Lucas B.

    (Yaba College of Technology, in Affiliation with University of Nigeria, Nigeria)

  • Aderemi Timothy Ayomitunde

    (Bells University of Technology, Nigeria)

Abstract

The critical need to create economic prosperity and ensure inclusive and equitable education and lifelong learning for all, especially in developing countries has been the motivation behind the various advocacies by the policymakers and other stakeholders in these countries to achieve the SDGs comes 2030. Meanwhile, ECOWAS sub region is characterized with the lowest human capital development alongside the highest rates of illiteracy in the world despite the continuous rise in government educational spending over the years. Against this backdrop, the role of government educational spending on human capital development in ECOWAS sub-region has been investigated with a view to driving one of the strategic goals of Sustainable Development- inclusive and equitable education and lifelong learning for all. In order to achieve this, annual data from 1990 to 2019 was utilized using a panel ARDL as a technique of estimation. The findings that emerged in this work are summarized as follows; the relationship between government educational spending and human capital development in ECOWAS sub region is more of a long run phenomenon. Therefore, government educational spending and human capital development have a positive and significant relationship in the long run. In the light of the above findings, this study therefore makes the following recommendations for the policymakers in ECOWAS sub region and by extension developing countries, any time the goal of these policymakers is inclusive and equitable lifelong learning via human capital development, the government at levels should embark on sustainable educational spending. In the same vein, these policymakers should be committed to funding of educational sector as stipulated by both the United Nations and the Abuja declaration of 2001, advocating for 26% of annual budget for educational sector in developing countries.

Suggested Citation

  • Oloke Emmanuel & Olanipekun Wahid Damilola & Mabinuori Oladotun Toriola & Ojo Lucas B. & Aderemi Timothy Ayomitunde, 2022. "Government Educational Spending and Human Capital Development in ECOWAS Sub-Region: Implication For Sustainable Development," Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, vol. 67(3), pages 37-52, December.
  • Handle: RePEc:vrs:subboe:v:67:y:2022:i:3:p:37-52:n:2
    DOI: 10.2478/subboec-2022-0014
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    References listed on IDEAS

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    More about this item

    Keywords

    Human Capital; Development; Government Educational Spending; ECOWAS; SDGs;
    All these keywords.

    JEL classification:

    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • H52 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • F63 - International Economics - - Economic Impacts of Globalization - - - Economic Development
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • 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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