The strong influence of sound corporate governance on economic Growth: evidence from Zimbabwe

  • Received June 1, 2017;
    Accepted June 22, 2017;
    Published September 1, 2017
  • Author(s)
    Alexander Maune
  • DOI
    http://dx.doi.org/10.21511/ppm.15(2-2).2017.13
  • Article Info
    Volume 15 2017, Issue #2 (cont. 2), pp. 445-455
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    5 articles
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

The study examined the impact of sound corporate governance on economic growth in Zimbabwe using an econometric model. A multiple linear regression analysis was employed to examine the relationship. Secondary data for the period 1968 to 2015 was collected from World Bank’s Worldwide Governance and World Development Indicators databases. It was found that sound corporate governance is significantly correlated to economic growth in Zimbabwe in a positive and negative manner with a p-value of 0.000023235 at 5% level of confidence. On one hand, control of corruption is negatively significantly related to economic growth and, on the other hand, political stability and absence of violence/terrorism positively significantly related to economic growth. Government effectiveness, regulatory quality, rule of law and voice and accountability are insignificant in influencing economic growth in Zimbabwe at 5% level of significance. The findings from this article will assist policy formulation, policy implementation and future research. This article, however, is of great importance to government, private sector and the academia.

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    • Figure 1. Investor Protection Indices for selected countries as of 2016
    • Table 1. Zimbabwe’s National Code of Corporate Governance structure
    • Table 2. Investor Protection Indicators
    • Table 3. Investor Protection Indices for selected countries as of 2016
    • Table 4. Explanations of variables used in the regression model
    • Table 5. Regression analysis, influence of sound corporate governance on economic growth in Zimbabwe
    • Table 6. Regression analysis, factor analysis – principal component extraction
    • Table 7. Stepwise regression analysis
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