Financial inclusion as a strategy for income inequality reduction and economic growth: PLS-SEM analysis based on cross-country evidence
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DOIhttp://dx.doi.org/10.21511/imfi.22(2).2025.36
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Article InfoVolume 22 2025, Issue #2, pp. 461-490
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This study examines the impact of financial inclusion, specifically the dimensions of access and usage, on income inequality and economic growth in 70 developing countries using data from 2014, 2017, and 2021. Drawing from multiple international databases, the study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess formative constructs of financial inclusion and to test the hypothesized relationships. Results show that financial access significantly reduces income inequality (β = –0.124, p < 0.05) and promotes economic growth (β = 0.261, p < 0.01). Similarly, financial usage has a negative effect on inequality (β = –0.223, p < 0.01) and a positive effect on growth (β = 0.412, p < 0.01). Among control variables, trade openness is associated with lower inequality, while population growth and corruption increase it; population growth also weakly hinders economic growth. The model explains 30.2% of the variance in income inequality and 45.6% in economic growth. The analysis distinguishes between upper-middle-income and lower-income groups, revealing that financial access is more impactful in wealthier developing countries, while usage is more influential in lower-income ones. These results underscore the need for income-specific policy design. To address concerns of generalization, additional descriptive country-level analysis was conducted for six selected countries, highlighting national-level variation in financial inclusion dynamics. Overall, the findings offer valuable insights for policymakers and international agencies seeking to design inclusive financial systems that support equitable growth and reduced inequality.
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JEL Classification (Paper profile tab)O15, G20, O47, D33, F43
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References55
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Tables11
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Figures33
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- Figure 1. SmartPLS results output
- Figure 2. G1 SmartPLS results output
- Figure 3. G2 SmartPLS Results Output
- Figure 4. Trends in financial inclusion, income inequality, and economic growth in Afghanistan (2014–2021)
- Figure 5. Trends in financial inclusion, income inequality, and economic growth in Burkina Faso (2014–2021)
- Figure 6. Trends in financial inclusion, income inequality, and economic growth in Benin (2014–2021)
- Figure 7. Trends in financial inclusion, income inequality, and economic growth in Kazakhstan (2014–2021)
- Figure 8. Trends in financial inclusion, income inequality, and economic growth in the Russian Federation (2014–2021)
- Figure 9. Trends in financial inclusion, income inequality, and economic growth in Thailand (2014–2021)
- Figure А1. Afghanistan Overview of Access, Usage, GDP per Capita, and Inequality
- Figure А2. Trends in GDP per Capita and Income Inequality (Gini Index) in Afghanistan (2014–2021)
- Figure А3. Trends in Financial Access in Afghanistan: Number of ATMs and Commercial Bank Branches (2014–2021)
- Figure А4. Trends in Financial Usage in Afghanistan: Account Ownership, Borrowing, and Saving (2014–2021)
- Figure А5. Burkina Faso Overview of Access, Usage, GDP per Capita, and Inequality
- Figure А6. Trends in GDP per Capita and Income Inequality (Gini Index) in Burkina Faso (2014–2021)
- Figure А7. Trends in Financial Access in Burkina Faso: Number of ATMs and Commercial Bank Branches (2014–2021)
- Figure А8. Trends in Financial Usage in Burkina Faso: Account Ownership, Borrowing, and Saving (2014–2021)
- Figure А9. Benin Overview of Access, Usage, GDP per Capita, and Inequality
- Figure А10. Trends in GDP per Capita and Income Inequality (Gini Index) in Benin (2014–2021)
- Figure А11. Trends in Financial Access in Benin: Number of ATMs and Commercial Bank Branches (2014–2021)
- Figure А12. Trends in Financial Usage in Benin: Account Ownership, Borrowing, and Saving (2014–2021)
- Figure А13. Kazakhstan Overview of Access, Usage, GDP per Capita, and Inequality
- Figure А14. Trends in GDP per Capita and Income Inequality (Gini Index) in Kazakhstan (2014–2021)
- Figure А15. Trends in Financial Access in Kazakhstan: Number of ATMs and Commercial Bank Branches (2014–2021)
- Figure А16. Trends in Financial Usage in Kazakhstan: Account Ownership, Borrowing, and Saving (2014–2021)
- Figure А17. Russian Federation Overview of Access, Usage, GDP per Capita, and Inequality
- Figure А18. Trends in GDP per Capita and Income Inequality (Gini Index) in Russian Federation (2014–2021)
- Figure А19. Trends in Financial Access in Russian Federation: Number of ATMs and Commercial Bank Branches (2014–2021)
- Figure А20. Trends in Financial Usage in Russian Federation: Account Ownership, Borrowing, and Saving (2014–2021)
- Figure А21. Thailand Overview of Access, Usage, GDP per Capita, and Inequality
- Figure А22. Trends in GDP per Capita and Income Inequality (Gini Index) in Thailand (2014–2021)
- Figure А23. Trends in Financial Access in Thailand: Number of ATMs and Commercial Bank Branches (2014–2021)
- Figure А24. Trends in Financial Usage in Thailand: Account Ownership, Borrowing, and Saving (2014–2021)
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- Table 1. Summary of the study variables
- Table 2. Descriptive statistics
- Table 3. Outer model results
- Table 4. Variance Inflation Factor (VIF) results
- Table 5. Hypothesis testing results (structural model)
- Table 6. Predictive power of the Model (R²)
- Table 7. G1 Results of the hypothesis testing (structural model)
- Table 8. G2 Results of the hypothesis testing (structural model)
- Table 9. Variance Inflation Factor (VIF) by income group
- Table 10. Predictive power of the Model (R²) by income group
- Table A1. List of countries included in the study sample
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