Foreign aid is very unpredictable. This unpredictability makes recipient government planning more challenging than it ought to be and lessens the value of aid. One of my research interests is the effect of aid volatility or large swings in aid on different political outcomes in recipient countries. One challenge of this work is conveying the magnitude of aid volatility.
The figure above is my current best attempt at showing just how volatile aid can be. Each year shows two bars, each representing an aid change in a country in sub-Saharan Africa in that year. The blue bars show the largest aid increases and the red bars show the most extreme aid decreases. I’m not particularly good at presenting data, so if you have criticisms please pass them along: @ryanbriggs.
The data used are ODA disbursements and I subtracted out technical assistance and debt relief. The sample of recipients contains all countries in sub-Saharan Africa between 1961 and 2008. I measured aid volatility as percentage changes from the aid level in the previous year. This way of measuring aid changes will produce large values if the previous year had an unusually small amount of aid. For example, Zimbabwe went from 0.46 million in aid in 1979 to 227.42 million aid in 1980, for an increase of roughly 49,000 percent. To avoid these situations, I dropped any observations where a country received less than 50 million dollars of aid. This means that all of the percentage changes in the figure above are happening on a base of at least 50 million (2008) USD of aid.
The figure reveals that each year some countries experience very large changes in aid. Social scientists often focus on averages—and average aid volatility is large enough that it is a problem—but the tails of this distribution are really scary. Each year of the figure shows two instances of real countries getting knocked around by aid changes, so I’d say that tails of the distribution matter. Some countries went from over 50 million in aid one year to less than 0 the next. Many other countries saw their aid double or triple in one year, and one saw a six-fold increase. How can a government plan future expenditures if a large fraction of their revenue can either quadruple or be cut in half. This is what is at stake in the calls for donor coordination to reduce aid volatility.
Update: For those who asked, I don’t have the data to measure aid changes as a percentage of government revenue or expenditure. To the best of my knowledge, these data do not exist across time for most of the countries in SSA. If I normalize aid changes as a percentage of GDP, I often see swings larger than +/- 5% of GDP.
A final note: it is hard to believe that these kinds of aid changes don’t affect recipient country politics, right?