How do aid and tax revenue affect government spending in Africa? Evidence from panel quantile regression

Start Date

27-3-2021 2:30 PM

End Date

27-3-2021 2:45 PM

Description

This study assesses the impact of aid and tax revenue on government spending in Africa. The study employs a panel quantile regression approach that minimises the sum of absolute deviation, thereby controlling for unobserved individual heterogeneity and heterogeneity at varying distributional levels. This approach enables to correct for endogeneity, dynamic panel data bias, misspecification and under or overestimation of parameters associated with the LS-type regression. The empirical findings reveal that the impact of aid and tax revenue, including other regressors are clearly heterogenous. In specific, the impact of aid on government spending supports the partial fungibility hypothesis in low spending countries and the degree of aid fungibility decreases with increasing aid inflow in high spending economies. The impact of tax revenue on government spending is also evidently heterogenous. Besides, the findings show that a lower level of tax revenue has more impact in less spending on economies than aid. However, higher tax revenue loses dominance and strength to aid at higher levels of government spending. This is in line with both the fiscal synchronisation hypothesis and the tax-spend hypothesis. In addition, trade openness, quality of life, well-being of people and quality of governance play an important role in the spending dynamics of economies especially high spending economies. However, there is little evidence of FDI inflows in influencing government spending in Africa. Moreover, the findings provide evidence of long-term persistence of aid and tax revenue across some distributional levels. In conclusion, the study is relevant policy recommendations to policymakers, economy managers and donors.

Recommended Citation

Dewortor, W. K. (2021, March). How do aid and tax revenue affect government spending in Africa? Evidence from panel quantile regression. Presented at the Postgraduate Conference on Interdisciplinary Learning: Re-Imagining Postgraduate Studies in the 21st Century and Beyond. Lingnan University, Hong Kong.

This document is currently not available here.

Share

COinS
 
Mar 27th, 2:30 PM Mar 27th, 2:45 PM

How do aid and tax revenue affect government spending in Africa? Evidence from panel quantile regression

This study assesses the impact of aid and tax revenue on government spending in Africa. The study employs a panel quantile regression approach that minimises the sum of absolute deviation, thereby controlling for unobserved individual heterogeneity and heterogeneity at varying distributional levels. This approach enables to correct for endogeneity, dynamic panel data bias, misspecification and under or overestimation of parameters associated with the LS-type regression. The empirical findings reveal that the impact of aid and tax revenue, including other regressors are clearly heterogenous. In specific, the impact of aid on government spending supports the partial fungibility hypothesis in low spending countries and the degree of aid fungibility decreases with increasing aid inflow in high spending economies. The impact of tax revenue on government spending is also evidently heterogenous. Besides, the findings show that a lower level of tax revenue has more impact in less spending on economies than aid. However, higher tax revenue loses dominance and strength to aid at higher levels of government spending. This is in line with both the fiscal synchronisation hypothesis and the tax-spend hypothesis. In addition, trade openness, quality of life, well-being of people and quality of governance play an important role in the spending dynamics of economies especially high spending economies. However, there is little evidence of FDI inflows in influencing government spending in Africa. Moreover, the findings provide evidence of long-term persistence of aid and tax revenue across some distributional levels. In conclusion, the study is relevant policy recommendations to policymakers, economy managers and donors.