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External Debt, Economic Complexity and Financial Development in Sub-Saharan Africa

Author

Listed:
  • Yve Daniel Ngassa Nya
  • Alex Kamgang Ndada
  • Alexis Tiomela Yemedjeu
  • Guy Paulin Dazoue Dongue

Abstract

The aim of this study is to investigate the role of external debt and economic complexity on the financial development in sub-Saharan Africa (SSA). The data used are annual, gathered from secondary sources, for 20 countries from 2002 to 2020. The analysis method uses the FGLS (Feasible Generalised Least Squares) and PCSE (Panel-Corrected Standard Errors) methods. This study reveals that external debt significantly and positively affects access to financial institutions, while it is negatively linked to the depth of financial markets. In contrast, economic complexity has a positive and significant influence on access to financial institutions, as well as on the depth of both financial institutions and financial markets. The policy implication of the findings is that policymakers should take into consideration the use of external debt as a means of finance for investments and implement policies that drive economic complexity with the aim of increasing financial development.

Suggested Citation

  • Yve Daniel Ngassa Nya & Alex Kamgang Ndada & Alexis Tiomela Yemedjeu & Guy Paulin Dazoue Dongue, 2025. "External Debt, Economic Complexity and Financial Development in Sub-Saharan Africa," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 7, pages 43-60.
    • Handle: RePEc:bas:econst:y:2025:i:7:p:43-60
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    More about this item

    JEL classification:

    • O55 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Africa
    • F34 - International Economics - - International Finance - - - International Lending and Debt Problems
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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