The effects of grants and loans on economic growth in Sub-Saharan Africa: Considering different types of income level

Abstract

This paper investigates the question of aid’s effects on economic growth in Sub-Saharan Africa (SSA) by disaggregating aid into grants and loans during 1994–2015. The estimation results indicate that grants have a positive and statistically significant effect on economic growth, while loans have a negative but insignificant effect on it. When we break down the panel data into Low Income Countries (LICs) and Middle Income Countries (MICs) in order to gain further insight, grants have been effective in spurring growth in both LICs and MICs, while loans have had positive and significant impact on economic growth in neither LICs nor MICs. Accordingly, the main findings of this study provide a consistent evidence in support of the grants-effectiveness on growth in both MICs and LICs, contrary to the ineffectiveness of loans. The other supplementary results show that the domestic investment (GCF) and education (SEC) which are basically public policy variables have significantly positive impacts on economic growth in MICs, while they are not statistically significant in LICs.

KEYWORDS:

• Grants
• loans
• economic growth
• SSA
• MICs
• LICs

JEL Classifications:

• C23
• F35
• O47
• O55

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 In our sample, the average per capita real GDP growth rate was 2.5% per annum in Sub-Saharan Africa during 1994–2015 (see Table A2 on the descriptive summary of the concerned variables).

2 There are related evidences for the importance of instability or uncertainty in SSA (Guillaumont, Guillaumont-Jeanney, and Brun 1999; Gyimah-Brempong and Traynor 1999).

3 According to the classification of the World Bank (2016), low income economies: Gross National Income (GNI) per capita ≤ $1005, lower middle income economies: $1006 ≤ GNI per capita ≤ $3955, upper middle income economies: $3956 ≤ GNI per capita ≤$12,235.

4 Clemens et al. (2012) noted the importance of modeling the lags involved in aid effectiveness. That is, it may take time for aid to affect growth.

5 With many panels and few periods, the GMM-SYS econometric technique is used to discover the most appropriate specification for analyzing the aid-growth link, which enhances the GMM-DIF estimation. This estimation technique integrates the first difference of the strictly exogenous variable as the standard instrument to remove the panel level effects, and the lags of the level or the difference of the dependent variable as GMM-type instruments to instrument the lagged dependent variables (Blundell and Bond 1998).

Additional information

Funding

This work was financially supported by National Research Foundation of Korea (NRF-2016-S1A5A2A03925644).