Foreign capital inflows, trade openness and output performance in selected sub-Saharan African countries

  • Received December 9, 2021;
    Accepted March 10, 2022;
    Published March 17, 2022
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.19(1).2022.18
  • Article Info
    Volume 19 2022, Issue #1, pp. 236-246
  • TO CITE АНОТАЦІЯ
  • Cited by
    1 articles
  • 641 Views
  • 251 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

This study empirically examined the dynamic impact of foreign capital inflows and trade openness on output performance and national productivity in 31 selected countries in sub-Saharan Africa (SSA) between 1985 and 2018. The study employed random effects and fixed effects models to estimate the coefficients. However, the results from the two models portray similar behaviors. Both estimates revealed a significant relationship between output performance and the independent variables. This suggests that the macroeconomic variables examined are good explanatory variables for analyzing the determinants of output performance and national productivity in the SSA region. The study further found that foreign capital inflows, trade openness and inflation rate have a positive and significant influence on output performance and national productivity. In contrast, exchange rate and interest rate exhibited a negative and significant relationship with such output performance. This result implies that policymakers in SSA countries must formulate policies that can successfully ensure trade openness and promote foreign capital inflows so as to stimulate national productivity and boost output performance in the region. Therefore, it can be concluded that foreign capital inflows and trade openness affect the industrial sector in contributing to output performance and national productivity in the SSA countries.

view full abstract hide full abstract
    • Table 1. Summary statistic results
    • Table 2. Correlation matrix
    • Table 3. LLC, IPS and Augmented ADF unit root tests
    • Table 4. Fixed effects test result
    • Table 5. Random effects test result
    • Table 6. Hausman test results
    • Conceptualization
      Noel Damson Nthangu, Koye Gerry Bokana
    • Data curation
      Noel Damson Nthangu, Koye Gerry Bokana
    • Formal Analysis
      Noel Damson Nthangu, Koye Gerry Bokana
    • Funding acquisition
      Noel Damson Nthangu, Koye Gerry Bokana
    • Investigation
      Noel Damson Nthangu, Koye Gerry Bokana
    • Methodology
      Noel Damson Nthangu, Koye Gerry Bokana
    • Project administration
      Noel Damson Nthangu, Koye Gerry Bokana
    • Resources
      Noel Damson Nthangu, Koye Gerry Bokana
    • Software
      Noel Damson Nthangu, Koye Gerry Bokana
    • Supervision
      Noel Damson Nthangu, Koye Gerry Bokana
    • Validation
      Noel Damson Nthangu, Koye Gerry Bokana
    • Visualization
      Noel Damson Nthangu, Koye Gerry Bokana
    • Writing – original draft
      Noel Damson Nthangu, Koye Gerry Bokana
    • Writing – review & editing
      Noel Damson Nthangu, Koye Gerry Bokana