Since 2010, over 50 countries have launched and begun implementing (or are currently developing) national financial inclusion strategies (NFIS). Financial inclusion is thus a facilitator and accelerator for broader economic growth and resilience, improved financial health, and employment creation and development. This implies that economies with higher financial inclusion are significantly lower than developing countries poverty rates.
Estimates from a cross-sectional OLS regression suggest a marginally significant association, although a negative sign holds, suggesting financial inclusion may be less effective over the long run at reducing income inequality in developing countries. The fixed-effect estimates suggest that per capita real GDP, the age-dependency ratio, inflation rates, Internet usage rates, and income inequality all have significant effects on levels of financial inclusion in developing countries. The fixed effect estimates for 3 years on average indicate financial inclusion is very important for the reduction of income inequality in developing countries, with the results being robust to different models. The fixed effects estimates indicate that the financial inclusion interaction terms with GDP growth and the ratio of enrollments at secondary schools are statistically significant, whereas the financial inclusion interaction terms with income inequality measured through Gini coefficients, income per capita, the rule of law, and inflation rates are statistically not significant for poverty in developing countries.
Calculating a Gini coefficient does not vary depending on the size of an economy, the way in which it is measured, or the wealth of a country. For instance, because of the similar income distribution, rich and poor countries can show similar coefficients. In some cases, the coefficients can be similar for countries that have a different income distribution, but have the same income levels. For instance, smaller countries, or those with lower economic diversity, often tend to exhibit lower coefficients, whereas larger, economically more diverse countries typically exhibit higher coefficients.
Importantly, the model also projects that inequality in wealth and financial literacy would emerge endogenously, without having to rely on the assumption of cross-sectional differences in preferences or on other substantive changes to the theoretical setting.12 Furthermore, differences in wealth between educational groups also emerge endogenously; i.e., certain subgroups of the population are optimally poor financial literacy, especially those who expect substantial income from a safety net in later life. Importantly, the model also predicts that inequality in wealth and financial knowledge will arise endogenously without having to rely on assumed cross-sectional differences in preferences or other major changes to the theoretical setup.12 Moreover, differences in wealth across education groups also arise endogenously ; that is, some population subgroups optimally have low financial literacy, particularly those anticipating substantial safety net income in old age.13 This forecast agrees with the hypothesis of Jappelli and Padula (2013), who suggest that the most economically uninformed individuals would reside in countries that offer the most generous welfare benefits (see also Jappelli 2010). They further propose that countries with generous Social Security benefits will have less incentive to save and build wealth, and, by extension, fewer reasons to invest in financial literacy.
