Income status is no basis for aid allocation decisions


The second half of 2014 will see the members of the OECD’s Development Assistance Committee (DAC) decide which developing countries will no longer be eligible to receive official development assistance (ODA) from 2015.

Who can get ODA?

Only the hardiest are likely to have delved deep enough into the OECD website to know how the DAC decides whether a country can receive ODA. They would have found that its decisions about which countries are on the ‘ODA eligibility list’ has historically been based almost solely on the World Bank’s ‘high income’ status category. The eligible list also excludes G8 members, EU members and those “with a firm date” for EU entry, but includes all Least Developed Countries (LDCs) regardless of their average income level.

Countries classified as high income for three consecutive years at the time of the DAC’s three-yearly review are taken off the list. The following year, they can no longer receive aid. Governments can continue to provide cooperation to such countries, but this would not count as ODA – nor would it count towards the UN-endorsed 0.7% of national income target.

Based on the World Bank’s latest annual update of GNI per capita for developing countries issued on 1 July, St Kitts & Nevis alone will come off of the list in 2015. If the DAC does not change its approach before 2017’s three-yearly review, then three more countries – Antigua & Barbuda, Chile and Uruguay – will stop being eligible to receive ODA.[1]  While there are no extreme poverty data for two of these four countries, Chile and Uruguay still have extreme poverty albeit relatively low levels (estimated at 1.4% or 0.2% respectively on the latest World Bank data). Interestingly, China’s average income, at US$6,560, is only about halfway to the high income threshold.

Income groups and resource allocation

As we argued in our 2013 report Investments to End Poverty, ‘middle income’ status is not a sensible basis for allocation decisions. We highlighted the fallacy of classifying countries by their average income as an oversimplification masking vastly different levels of income within countries (see also Charles Kenny’s blog which argues on this issue).

Similarly, high income status is unlikely to be the best way to decide whether a country might still need aid. The high income threshold of US$12,746 in 2013 is based on a decision by the World Bank  in 1989 to re-classify all ‘industrial’ countries as high income, with the threshold used increased each year in line with global prices. It is not clear that this is the best basis for deciding whether a country might still need ODA.

Even otherwise relatively ‘rich’ countries may have persistent pockets of people living in deep poverty aside relative affluence. In such cases, some forms of technical cooperation might be helpful. A rich government may simply choose not to help its poorest people – or a formerly rich but crisis-torn country may suddenly find itself unable to do so. Should poor people in such countries be denied access to ODA? It is also unclear what happens if a country’s GNI falls below the high income threshold: can they be added back onto the eligible list?

Better ODA allocation for the post-2015 development agenda?

As part of the ongoing reappraisal of ODA (declaration of interest: our Executive Director, Judith Randel, is on a group of experts advising the DAC on this agenda), the DAC are also exploring whether recipient eligibility criteria should be reviewed.

At DI we believe that resource allocation should focus on the greatest need, based on good data. Allocation decisions need to account for incidence of poverty and access to domestic and international resources. Average income is simply not a good basis to make such important decisions.

Even the World Bank itself accepts that average income alone “does not completely summarise a country’s level of development or measure welfare”,[2] and states that these income group ‘analytical categories’ are not used for allocation decisions. The World Bank is in the process of reviewing its income classifications: it seems to have been taken aback by their use elsewhere “as the basis for policy decisions”. The DAC’s eligible list is one such example: it specifically assigns countries to these income groups.

Decisions about countries’ ODA eligibility need to be more sophisticated. As an example, the UN has a multi-dimensional approach for determining the ‘Least Developing Countries’ (LDCs). There is also an inbuilt ‘graduation’ process spanning almost a decade to prepare countries for loss of LDC status.

As ODA is the only international resource that can be directly targeted at the poorest people, poverty levels should play a role in eligibility decisions. The DAC should also consider the availability of other resources, both domestic capacity and wider resource flows beyond ODA. This would, of course, require a revolution in the quality, quantity and timeliness of data needed to support these decisions. There could also be a clearer system of graduation from ODA eligibility to prepare for the loss of a valuable resource.

With a post-2015 development agenda likely to be rooted in not just economic but also environmental and social development, we will need to understand countries through a much wider lens. Average national income looks particularly partial and anachronistic under such a view.

So time to tell the DAC: it’s time for change!

DI will be releasing an in-depth piece on ODA modernisation in the coming weeks. For more information please contact Cordelia Lonsdale (cordelia.lonsdale@devinit.org) and Ian Townsend (ian.townsend@devinit.org).



1. Latvia, Lithuania and Russia were high income in 2012 and 2013, but are already ineligible as EU/G8 members. No country was high income in 2013 only (see the World Bank’s historical GNI per capita spreadsheet and 2013 data PDF).

2. “Why use GNI per capita to classify economies into income groupings?”, World Bank knowledge base article (undated). Though it goes on to say it remains a “useful and easily available indicator that is closely correlated with other […] measures of the quality of life”.