Recent literature in the meta-analysis category where results from a range of studies are brought together throws doubt on the ability of foreign aid to foster economic growth and development. This article assesses what meta-analysis has to contribute to the literature on the effectiveness of foreign aid in terms of growth impact. We re-examine key hypotheses, and find that the effect of aid on growth is positive and statistically significant. This significant effect is genuine, and not an artefact of publication selection. We also show why our results differ from those published elsewhere.
We provide new evidence on the impact of social protection interventions on household size and the factors that cause the household size to change: fertility, child fosterage, and in and out migration related to work and marriage. Using data from an intervention delivered at scale, Ethiopia's Productive Safety Net Program (PSNP), we find that participation in the PSNP leads to an increase in household size of 0.3 members. We find no evidence that PSNP participation increases fertility and some evidence that fertility is reduced, specifically it reduces the likelihood that an adult female member gives birth by 8.1 percentage points. We reconcile this seemingly divergent findings by showing that the increase in household size arises from an increase in the number of girls aged 12 to 18 years. We present evidence that this occurs because the PSNP causes households to delay marrying out adolescent females.
As research on the empirical link between aid and growth continues to grow, it is time to revisit the accumulated evidence on aid effectiveness. This paper extends previous meta-analyses, noting that the availability of more data enables us to conduct a sub-group analysis by disaggregating the sample into different time horizons and assess if there are temporal shifts in aid effectiveness. The new and updated results show that the earlier reported positive evidence of aid’s impact is robust to the inclusion of more recent studies and this holds for different time horizons as well. The authenticity of the observed effect is also confirmed by results from funnel plots, regression-based tests, and a cumulative meta-analysis for publication bias.
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