The effect of aid on growth: Evidence from a quasi-experiment

Sebastian Galiani, Stephen Knack, Lixin Colin Xu, Ben Zou

A key problem in exploring how foreign aid affects economic growth is the endogeneity of aid in growth models. This column tackles the problem by exploiting an income threshold which, though arbitrary, is a key criterion in allocating scarce foreign aid resources. The evidence shows that, among poor countries where it is a large source of funding, foreign aid increases short-run economic growth.

There is heated debate over the question of whether foreign aid generates economic growth in recipient countries. Identification of the causal effect of aid on growth has been elusive, due to the endogeneity of aid in growth models. An instrumental variable is needed to address these problems. However, as Clemens et al. (2012) conclude in their recent assessment: “the aid-growth literature does not currently possess a strong and patently valid instrumental variable with which to reliably test the hypothesis that aid strictly causes growth.”

New research

In a new paper (Galiani et al. 2016), we contribute to this literature by instrumenting the endogenous aid variable (in an economic growth equation) by exploiting a plausible quasi-experiment created by the income threshold set by the International Development Association (IDA), the World Bank’s programme of grants and concessionary loans to low-income countries

This income threshold has been used as a key criterion in allocating scarce IDA resources since 1987, and is adjusted annually to take account of inflation. Other major donors also appear to use the IDA threshold as an informative signal about where development aid is most needed, and we show that total aid declines significantly once a recipient country crosses the IDA income threshold from below. The IDA threshold is nevertheless an arbitrary income level that does not necessarily represent any structural change in economic growth.

Using a sample of 35 countries that crossed the IDA threshold from below between 1987 and 2010, we find that a 1% increase in the aid-to-GNI ratio raises the annual real per capita short term GDP growth rate by 0.031 percentage points. The mean aid-to-GNI ratio at the crossing is 0.09, so a one percentage point increase in the aid-to-GNI ratio raises annual real per capita GDP growth by approximately 0.35 percentage points. This effect is about 1.75 times as large as those reported by Clemens et al. (2012). Using OLS with fixed effects and lagging aid by a period, they find that a one percentage point increase in aid/GDP (at aid levels similar to our sample mean) is followed by at most a 0.2 percentage-point increase in growth of real GDP per capita. We find similar-sized effects in our sample, without instrumenting for aid but merely lagging it by a period and including fixed effects.

The sizable effect of aid on growth we find may be attributable in part to the fact that our sample consists of low-income countries that successfully crossed the IDA threshold at some point between 1987 and 2010. Aid may have been more effective in these countries – for example, due to better economic policies and lower corruption – than in countries remaining below the threshold.

A simple growth accounting exercise and the coefficient on aid in investment regressions suggest that investment could be an important channel through which aid affects growth. We show that the investment rate drops following the reduction in aid. Increasing the aid to GNI ratio by one percentage point increases the investment to GDP ratio by 0.54 percentage points, although this coefficient is generally not significant. The magnitude of the effects on growth and investment is consistent with the average capital stock to GDP ratio for the sample countries, which we estimate to be approximately two.

As in most of the literature relying on panel data covering a short period of time, we estimate the short-run effect of aid on growth, an effect that mainly operates through physical investment. In the long run, aid could affect growth through several other channels, but its identification requires exogenous changes in aid over a very long period of time. Our instrument does not provide such exogenous variability to estimate that parameter.

Conclusions

Needless to say, identification of causal effects is a daunting task—especially at the macroeconomic level—so all causal estimates of country level parameters should be interpreted cautiously. Still, at the micro level, researchers need to evaluate on a case by case basis which aid projects work better, if at all.

Our evidence shows that, overall, foreign aid increases economic growth among poor countries where aid is a large source of funding. Moreover, even at the macro level, aid may have heterogeneous effects depending on recipient characteristics, aid modalities, and donor motives (Mekasha and Tarp 2013). For example, aid provided by some bilateral institutions for political or commercial reasons may be less effective (Dreher et al. 2014), and may be less sensitive to crossing the IDA threshold. Our relatively large effect may apply to less politicised aid. Following the end of the Cold War, however, the share of aid that is highly-politicised has arguably fallen significantly, with geopolitical motives declining in importance relative to developmental concerns (Headey 2008).

Our relatively small and homogeneous sample is not ideal for testing heterogeneous effects of aid. Moreover, because we identify only the effect of aid on growth in the short term, our evidence does not contradict any view of aid’s effects on long-term development. Despite these caveats, we believe our evidence contributes to understanding the effect of aid on economic growth in the short-term for poor countries that are financially constrained.

Our results also contribute to the empirical literature on donors’ aid allocation decisions across recipient countries (e.g. Alesina and Dollar 2000, Chong and Gradstein 2008). Specifically, they support the conjecture by Moss and Majerowicz (2012) that bilateral donors use IDA policies – and specifically its income eligibility threshold – as an informative signal of recipient need. Patterns of donor ‘herding’ measured by Frot and Santosi (2011) may be partially due to donors’ common responses to recipient countries’ crossing the IDA income threshold.

References

Alesina, A and D Dollar (2000) “Who gives foreign aid to whom and why?” Journal of Economic Growth, 5: 33-64.

Chong, A and M Gradstein (2008) “What determines foreign aid: The donors’ perspective”, Journal of Development Economics, 87: 1-13.

Clemens, M A, S Radelet, R R Bhavnani and S Bazzi (2012) “Counting chickens when they hatch: The short-term effect of aid on growth”, Economic Journal, 122(561): 590-617.

Dreher, A, V Eichenauer and K Gehring (2014) “Geopolitics, aid and growth”, University of Heidelberg, Department of Economics, Discussion Paper Series, No. 575.

Frot, E and J Santiso (2011) “Herding in aid allocation”, Kyklos, 64(1): 54-74.

Galiani, S, S Knack, C Xu and B Zou (2016) "The effect of aid on growth: Evidence from a quasi-experiment", NBER Working Paper 22164.

Headey, D (2008) “Geopolitics and the effect of foreign aid on economic growth: 1970-2001”, Journal of International Development, 20: 161-180.

Mekasha, T J and F Tarp (2013) “Aid and growth: What meta-analysis reveals”, Journal of Development Studies, 49(4): 564-83.

Moss, T and S Majerowicz (2012) “No longer poor: Ghana’s new income status and implications of graduation from IDA”, Center for Global Development Working Paper 300, Washington, DC.