Consequences of Aid Volatility for Macroeconomic Management and Aid Effectiveness
This paper reviews both the literature on aid volatility and also adds to that literature. In general, the focus of this literature has been on the volatility of overall aid, while we focus more on the volatility of the individual aid sectors, e.g., education aid. In doing this, detailed use is made of the Creditor Reporting System (CRS) database on aid commitments and disbursements, particularly the latter. Key aid sectors in explaining total aid volatility relate to debt, programme assistance, infrastructure and government. This reflects both these sectors’ volatility and their size. The most volatile aid sectors per se are debt, industry, humanitarian, NGO and programme assistance. The least volatile are education, health, other social infrastructure and multi-sector aid. We also find evidence that the volatility of different aid sectors saw a peak around 2006, which was about when debt aid volatility was at its highest. In an asymmetric VAR, we find that both positive and negative aid volatility tend to be corrected for in the following period, rather than there simply being a return to trend. There are also cross-sector effects by which volatility in one sector has subsequent impacts on other sectors. These tend to revolve around government aid and programme assistance. Finally we examine the impact of aid and aid volatility on very specific targets, finding both to be significant. There are several lessons we draw from this: first, in analysing aid’s impact, for example, on social targets such as school completion rates, social sector aid rather than overall aid is the relevant variable although not necessarily just education aid. Second, we argue that a complete understanding of aid’s impact can only be obtained by an analysis such as this, across a range of targets and then analysing the impact of these targets on the macroeconomy itself. This leads to the further conclusion that it is not the volatility of total aid which matters so much as the sum of sector and subsector volatilities.