Nexus between corruption, market capitalization, exports, FDI, and country’s wealth: A pre-global financial crisis study

  • Received April 11, 2022;
    Accepted October 27, 2022;
    Published November 21, 2022
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  • Article Info
    Volume 20 2022, Issue #4, pp. 224-237
  • Cited by
    5 articles

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

The study investigates the impact of corruption, market capitalization, exports, and foreign direct investment on the wealth of 178 countries worldwide. Thus, the paper uses univariate and multivariate regressions to observe the nexus among exports, foreign direct investment, market capitalization, corruption, and wealth of nations. The findings indicate that corruption poses a significant hindrance to prosperity and development, as evaluated with respect to the Transparency International Corruption Perceptions Index. Additionally, the results showed that the world’s poorest nations are becoming less corrupt while the wealthiest ones are growing more corrupt. The paper also concludes that exports and market capitalization are critical for prosperity and development when combined with lower corruption levels. Furthermore, the analysis also suggests that inbound foreign direct investment favors the development of emerging countries. Surprisingly, market capitalization and exports had little impact on wealth of countries before the crisis period. Moreover, integrity also fosters economic growth. Overall, the study concludes that the causes of wealth are country-specific.

I thank the editor and the reviewers for the helpful comments and suggestions that significantly enhanced this work. The usual disclaimer applies.

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    • Figure 1. Interactions between measures in 2008 and wealth
    • Figure 2. Interactions between changes in the values of measures and wealth
    • Table 1. List of countries
    • Table 2. Example countries by the category of wealth
    • Table 3. Descriptive statistics for 2008
    • Table 4. Descriptive statistics for 2005
    • Table 5. Pearson correlation matrix for each of the six variables for 2008
    • Table 6. Pearson correlation matrix for each of the five variables for 2005
    • Table 7. Main results for Model 1
    • Table 8. Main results for Model 2
    • Table 9. Countries, by wealth, included in ANOVA 1
    • Table 10. Countries, by wealth, included in ANOVA 2
    • Table 11. The fastest-growing nations in the world
    • Conceptualization
      Mamdouh Abdulaziz Saleh Al-Faryan
    • Data curation
      Mamdouh Abdulaziz Saleh Al-Faryan
    • Formal Analysis
      Mamdouh Abdulaziz Saleh Al-Faryan
    • Funding acquisition
      Mamdouh Abdulaziz Saleh Al-Faryan
    • Investigation
      Mamdouh Abdulaziz Saleh Al-Faryan
    • Methodology
      Mamdouh Abdulaziz Saleh Al-Faryan
    • Project administration
      Mamdouh Abdulaziz Saleh Al-Faryan
    • Resources
      Mamdouh Abdulaziz Saleh Al-Faryan
    • Software
      Mamdouh Abdulaziz Saleh Al-Faryan
    • Supervision
      Mamdouh Abdulaziz Saleh Al-Faryan
    • Validation
      Mamdouh Abdulaziz Saleh Al-Faryan
    • Visualization
      Mamdouh Abdulaziz Saleh Al-Faryan
    • Writing – original draft
      Mamdouh Abdulaziz Saleh Al-Faryan
    • Writing – review & editing
      Mamdouh Abdulaziz Saleh Al-Faryan