At the G8 summit in Gleneagles in 2005 donors agreed to scale up official development assistance substantially to finance important dimensions of pro-poor growth, notably the education- and health-related targets enshrined in the so-called Millennium Development Goals of 2000. Donors paid heed to advocates such as Sachs and McArthur (2005) who reckon that aid is a critical constraint to finance “what is crushingly expensive for the poorest of the poor”. Increases in foreign aid, if properly directed, could enhance the poverty-reducing impact of a given rate of economic growth. Less inequality could, in turn, strengthen social cohesion and ensure political stability.
If only foreign aid was properly directed and actually reached the poor! Horror stories of massive looting rather suggest that privileged local elites divert aid for personal benefit, with former presidents Mobutu Sese Seko in Zaire, Mohamed Suharto in Indonesia, and Ferdinand Marcos in the Philippines figuring most prominently. The simple correlation between net aid transfers (in percent of the recipient country’s GDP) and the Gini coefficient on income inequality across countries does not provide a clear picture on whether it is primarily the rich or the poor who derive benefits from foreign aid (Figure 1).
Figure 1. Aid and inequality across 21 recipient countries (average over 1970–95)
Source: Herzer and Nunnenkamp (2012).
In a recent paper (Herzer and Nunnenkamp 2012) we enter largely unexplored territory by making the case for causal effects of increased aid on widening income gaps within the recipient countries.1 We employ panel cointegration techniques to examine the long-run effect of net aid transfers, relative to the recipient countries’ GDP, on the estimated household income inequality available in Gini format from the University of Texas Inequality Project. The analysis covers 21 recipient countries with continuous and consistent data on inequality over the period 1970–95. Panel cointegration estimators are most appropriate in the context of identifying causal effects of aid. They are robust (under cointegration) to several estimation problems that often plague empirical work, including omitted variables, slope heterogeneity, and endogenous regressors. Importantly, no other variables are required to produce unbiased estimates of the long-run causal relations between aid and inequality.2 This holds when both time series are non-stationary (or, more precisely, integrated of the same order) and form a cointegrated pair. Extensive pre-tests reveal that these two conditions are fulfilled.
To assess the long-run effect of aid on income inequality, we use panel cointegration estimators suggested by Pedroni (2001) which account for the endogeneity of aid and allow the estimated coefficients to differ across countries (slope heterogeneity). The effect of aid proves to be statistically significant and positive. According to our preferred estimate, an increase in the aid-to-GDP ratio by one percentage point leads to an increase in the Gini coefficient by 4.2 units. This effect is quantitatively important. The average aid-to-GDP ratio for the 21 sample countries is slightly above 2%. Taken at face value, scaling up aid by about half that ratio would widen income inequality to the degree of almost one quarter of the difference in the Gini coefficients between the two extreme values reported for Malta (34) and Kuwait (51.9).
Moreover, the inequality-increasing impact of aid proves to be fairly robust. Specifically, the major result holds when employing alternative panel cointegration estimators, accounting for possible structural breaks in the data for specific recipient countries during the period of observation, using different sources of data on income inequality, and excluding one country at a time from the sample. With all these modifications the coefficient on foreign aid remains significantly positive, revealing widening income gaps within recipient countries.
Our study captures overall effects which cannot necessarily be attributed to a single channel through which aid widens income gaps. Starting with Svensson’s (2000) seminal contribution, the effects working through rent seeking and corruption in the recipient countries have received most attention in the literature. Local elites and rich population segments easily get the upper hand in rent-seeking contests over common-pool resources. Almost by definition, local elites are endowed with a disproportionate share of the country’s economic and political power. At the same time, the transfer that a group receives tends to be proportional to its expenditures on rent-seeking as a fraction of total expenditures on rent-seeking by all groups. Taken together, aid-induced rent-seeking favours the rich.
In contrast to public opinion in donor countries, however, it is not only corruption and rent-seeking in the recipient countries to blame. The behaviour of donors, too, bears responsibility for the inequality-increasing effects of aid. From the literature on aid allocation across recipient countries, it is known that donors are not purely altruistic. According to Alesina and Dollar (2000), there is “considerable evidence that the direction of foreign aid is dictated as much by political and strategic considerations, as by the economic needs and policy performance of the recipients”. Selfish donor motives are likely to impair the needs- and merit-based allocation of aid within countries, too. For instance, aid in the area of physical infrastructure may be guided by commercial interests and concentrate in industrial clusters rather than remote areas where the poorest people are living. Using aid as a means to buy political support by the local elite implies that it favours the rich rather than the poor within a particular country.3
Furthermore, aid agencies have incentives to ‘push money out the door.’ Consequently, they favour large-scale operations over small projects, even though the latter may be better suited to reducing inequality. Agencies are inclined to ‘plant their flag’ and engage in highly visible projects in order to secure future funding. This may explain why various donors prefer granting aid for higher levels of education, but spend little on primary education, even though the Millennium Development Goals require donors to concentrate on universal access to basic education as a pre-condition for pro-poor growth. Organisational imperatives related to future funding are also likely to weaken the incentives of aid agencies to operate in remote regions where aid would be needed most. It is easier to demonstrate immediate and visible results to political authorities in the donor country when addressing less entrenched forms of poverty. Inequality-reducing effects of aid become less likely, however, if risk-averse agencies are reluctant to work in difficult environments.
All in all, there is little reason for being optimistic and expecting foreign aid to be effective in alleviating poverty in recipient countries even if it had no discernible average growth effects. Calls on donors to strengthen the conditionality of aid, focus on countries with less corruption and better governance, and prevent leakage by stricter monitoring and closer involvement of the poor in aid delivery are insufficient even if such measures help restrict local rent-seeking. Better accountability is also required on the part of donors. Aid agencies tend to ignore their own incentive problems which prevent aid from reducing inequality. Public outrage in the North about corruption in the South abstracts from the selfish aid motives that lead donors to favour rich local elites. Overcoming the gap between the donors’ rhetoric on pro-poor growth and inequality-increasing aid allocation is no easier than overcoming rent-seeking and leakage in the recipient countries.
Alesina, A and D Dollar (2000), “Who gives foreign aid to whom and why?”, Journal of Economic Growth 5: 33–63.
Bjørnskov, C (2010), “Do elites benefit from democracy and foreign aid in developing countries?” Journal of Development Economics 92:115–24.
Chong, A, M Gradstein and C Calderon (2009), “Can foreign aid reduce income inequality and poverty?”, Public Choice 140: 59–84.
Doucouliagos, H and M Paldam (2009), “The aid effectiveness literature: The sad results of 40 years of research”, Journal of Economic Surveys 23: 433–61.
Herzer, D, P Nunnenkamp (2012), “The effect of foreign aid on income inequality: Evidence from panel cointegration”, Working Paper 1762. Kiel Institute for the World Economy, Kiel.
Pedroni, P (2001), “Purchasing power parity tests in cointegrated panels”, Review of Economics and Statistics 83: 727–31.
Sachs, J D and J W McArthur (2005), “The Millennium Project: A plan for meeting the Millennium Development Goals”, Lancet 365: 347–53.
Svensson, J (2000), “Foreign aid and rent-seeking”, Journal of International Economics 51, 437–61.
1 In contrast to the large literature on the growth effects of foreign aid, the distributional effects have received hardly any attention. Major exceptions include Chong et al (2009) and Bjørnskov (2010). Chong et al find that aid has no robust effect on inequality. According to Bjørnskov, aid is associated with higher inequality in more democratic recipient countries.
2 Of course, several factors other than aid affect income inequality. However, the existence of further cointegrating relationships does not affect our results on net aid transfers.
3 In addition, foreign aid in the past often took the form of structural adjustment loans. Critics of conditional aid argue that these loans had negative distributional effects, eg, by involving cuts in local government spending on poverty relevant items such as basic education and health.