In this paper, we reassess the relationship between foreign aid and income inequality. The existing literature provides mixed evidence at best on the direction, magnitude, and significance of the relationship between foreign aid and income inequality. We contribute to the literature on this topic by differentiating between types of foreign aid namely: economic, social, production, multi‐sector, and humanitarian aid to determine which types of foreign aid reduce income inequality in recipient countries after accounting for endogeneity bias using generalized method of moments estimation method. We also study the role of control of corruption in the aid‐inequality relationship. The study uses panel data comprising of 78 recipient countries for the last 14 years. We found that an increase in total aid increases income inequality, however, when we differentiate among types of aid, we found that the economic sector, production sector, and humanitarian aid decrease income inequality, multi‐sector increases income inequality while social aid does not have any impact on income inequality. Moreover, we found that foreign aid has a negative relationship with income inequality when its interaction with corruption is included in the model. This result holds for all types of foreign aid. Negative interactions between foreign aid and corruption show that foreign aid reduces income inequality in countries where control for corruption is high.
The present study aims to evaluate the impact of foreign assistance on income inequality of selected developing economies. Panel co-integration technique is applied for the purpose of estimation. After confirming the pre-conditions for cointegration, we have applied the Fully Modified-OLS method to estimate the association between foreign aid and income inequality. Controlling for other variables, we find a positive and significant association between foreign aid and inequality. The empirical results are robust concerning the sub-samples of developing economies selected according to the income classification of the World Bank. The empirical results are also robust concerning the alternative measure of income inequality.
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