Authors : José Maria Larrú and Carlos Quesada González
Affiliated organization : Multidisciplinary Digital Publishing Institute (MDPI)
Type of publication : article
Date de publication : December 2021
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Introduction
The aim of this article is to shed light on the effectiveness of Official Development Assistance (ODA) to reduce poverty. The 2030 Agenda for Sustainable Development has emphasized that people, prosperity, peace, planet, and partnerships are the “5 Ps” that summarize the framework under the Sustainable Development Goals, which should be reached for our world to be transformed. The opposite of prosperity is poverty (another “P”). The preamble of the Agenda clearly states: “We recognize that eradicating poverty in all its forms and dimensions, including extreme poverty, is the greatest global challenge and an indispensable requirement for sustainable development”. There are many ways and financial resources to reach this goal. Among others, economic growth and external flows such as ODA (or foreign aid) from donor countries to the most needy developing countries may be one of the more effective. However, are donors considering poverty “under its all forms and dimensions” as the real and main reason for allocating their ODA funds?
ODA Quality
There are some quality indicators of ODA collected by surveys conducted by the Global Partnership for Effective Development Cooperation. The indicators show that the quality of ODA is not bad, broadly speaking. The best practices seem to be interventions that draw objectives from country-led results framework (the so-called ownership principle in the Paris Declaration for Effective Development Cooperation), the annual predictability of aid funds (not for medium-term) and the low levels of tied aid.
All in all, donor practices seem to be good enough for development in the three countries. We cannot infer that this is translated into a poverty reduction automatically, but it is a useful evidence for our purpose.
ODA Sectoral Distribution
In the case of Guinea, the sectoral composition for all donors has not changed a lot between the two periods. Social infrastructure leads the ODA (42%), Economic infrastructure has increased a little (from 7% to 11%) and there has been some reductions in ODA for production (from 9% to 4%), in Multisector (specially in general environment protection) and in Debt relieve (from 20% to 17%). Some donor and sectoral specialization could be identified. For instance, European Union leads ODA for road transport (more than their 30% of ODA went to this sector). African Development Bank and IDA tend to concentrate their aid in Economic Infrastructure, whereas United Nations preferred to help Government and civil society, especially conflict, peace and security (14% of its ODA in 2010–2018).
All in all, donor practices seem to be good enough for development in the three countries. We cannot infer that this is translated into a poverty reduction automatically, but it is a useful evidence for our purpose
One remarkable feature for all donors is that they do not tent to send ODA flows to sectors related to multidimensional poverty indicators. The highest percentage of ODA channelled to dimensions directly related to causes of poverty was education (16% 2002– 2009). However, some donors tend to distribute their ODA more concentrated. For instance, education received 32% of IDA flows for 2002–2009, health 55% from other multilaterals (excluding EU, World Bank, IMF, regional development banks and UN). The IMF is clearly specialized in channelled its aid through General Budget Support (more than 80% in the two periods considered). Lastly, the UK focused a huge proportion of its aid to debt relive (33% in 2002–2009 and 69% in 2010–2018). It should bear in mind, that these amounts cannot be considered directly linked to poverty reduction. In fact, it is not “fresh money” for development agents, NGOs or practitioners.
Poverty Incidence and ODA Flows: Is There a Link?
The goal of this section is to try to relate development aid flows to changes in the 10 multidimensional poverty indicators. The hypothesis is that if a sufficient amount of aid has been produced in the sectors that are most closely related to poverty indicators, it could be expected that it has contributed in some way to said reduction. In cases where a possible impact is identified, we will look for which donor has been most responsible for this aid-poverty alleviation relationship.
Social infrastructure leads the ODA (42%), Economic infrastructure has increased a little (from 7% to 11%) and there has been some reductions in ODA for production (from 9% to 4%), in Multisector (specially in general environment protection) and in Debt relieve (from 20% to 17%)
Regarding the dimension of deprivation in education, Guinea and Liberia receive a similar amount (USD 200 million). Guinea also “profited” the aid well in terms of contribution to educational improvement, since with USD 196 million, it achieved a cumulative −4.9 points in educational poverty.
As regards health, it is complex to identify a representative sector of nutrition or infant mortality. In terms of nutrition, the reduction in Sierra Leone stands out (−3.4 points). It is possible that this aid could have contributed to the reduction of malnutrition in the country and partially explain this remarkable reduction of −3.4 points (in contrast to zero for Guinea and −1.5 for Liberia).
Guinea also “profited” the aid well in terms of contribution to educational improvement, since with USD 196 million, it achieved a cumulative −4.9 points in educational poverty
With regard to sanitation, there is a subsector directly related to it “basic sanitation” but which barely received funding (the largest was Guinea with 5.6 million, which is only 0.2% of its ODA). The same happens with “basic drinking water supply” where Guinea once again received the maximum but only 6.6 million.
Discussion
We have identified a positive cointegration between ODA and GDP (macro effect), but this result is not enough to show that ODA was an effective financial instrument to reduce multidimensional poverty when a sectorial and spatial analysis were carried out (meso or micro effect). In fact, the main findings of the paper are that, although a positive cointegration between ODA and GDP may be identified, ODA flows were not focused on the sectors that are more related to multidimensional poverty indicators and -at least in the case of Sierra Leone- neither on the districts where multidimensional poverty were higher.
The political economy consequence of our results is that the analysis of the aid-growth nexus is not enough to state the effectiveness of foreign aid and its contribution to reach SDGs targets. Our results, especially in the case study of Sierra Leone, show that country ownership, defined as “countries set their own national development priorities, and development partners align their support accordingly while using country systems” is still more a wish than a reality. Donors might take advantage of Sierra Leonean national multidimensional poverty index and data as a base line to align their ODA contributions, at least those that have the specific intention of reducing poverty (ODA for the poor). This would be a sign that the Global Partnership’s work is going further than the irrelevance.
Our recommendation to associate ODA projects and programmes to multidimensional poverty indicators might help to overcome the level of vagueness and rhetoric of the Partnership discourse
Linking ODA to MPI indicators can be a concrete and successful good practice in line with the Global Partnership Action Area 2.6. “strengthening development effectiveness at subnational level to achieve the SDGs”. The Partnership echoes the low capacity that cities, municipalities, local and regional authorities have to exert a real influence on donors allocations, but the Partnership only offers a space for dialogue and knowledge sharing on how to overcome the challenges that implementing the 2030 Agenda implies.
Our recommendation to associate ODA projects and programmes to multidimensional poverty indicators might help to overcome the level of vagueness and rhetoric of the Partnership discourse. We believe that linking ODA to multidimensional poverty indicators, disaggregated by space, groups, sex, ages and deprivations may be an effective contribution to “enhance international support for implementing effective and targeted capacity building in developing countries to support national plans to implement all the SDGs, including North-South, South-South and triangular cooperation”.
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