Pulling the purse strings: Are there sectoral differences in political preferencing of Chinese aid to Africa?

China is emerging as an increasingly important player in the global development space, but may be less bound to compacts that aim to curb political preferencing and therefore may produce less yield in terms of impact toward Sustainable Development Goals. This research tests the hypothesis that the disproportionate aid allocation to the birth regions of the current African political leaders that applies to some sectors more than others.

We applied a two-part model to first estimate the probability that a region receives an aid project. Then when at least one aid project is present in a leader's birth region, we estimated the mean amount of aid the region received.

This analysis covers 699 subnational units (first administrative level) across 44 African countries over 2000-2014. These administrative units were compiled into a region year panel resulting in 10,485 observations.

Birth regions of the current political leader are significantly more likely than the average of all of the regions to receive education (1.3 percentage points), social infrastructure and services (1.2 percentage points), and energy aid (1.7 percentage points). No significant association was found between aid flows to the birth region of the current political leader in the agriculture, communication, education, government, health or transportation sectors. Within the education sector, the coefficients for birth region are positive in both parts and statistically significant. Both the probability of aid allocation and the amount of aid conditional on any projects increase in the birth region of the current political leader.

This sector-specific analysis provides a more nuanced picture of Chinese aid than previous analyses that determine the presence of political preference according to aggregate aid flows. The sectors where political preferencing exists are also those sectors that are typically associated with limited counterfactual-based program evaluation. We present evidence that demonstrates the importance of disaggregating aid flows in order to support a new policy framework designed to target the Sustainable Development Goals.