Aid and Growth What Meta-Analysis Reveals

Some 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 paper assesses what meta-analysis has to say about the effectiveness of foreign aid in terms of the 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.aid and growth, meta-analysis, heterogeneity and publication bias

A Meta-Analysis of Aid Effectiveness: Revisiting the Evidence

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

Aid and Growth:What Meta-Analysis Reveals

Some 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 paper assesses what meta-analysis has to say about the effectiveness of foreign aid in terms of the 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

Aid and income: Another time-series perspective

This study provides a replication of the empirical results reported by Nowak-Lehmann, Dreher, Herzer, Klasen, and Martínez-Zarzoso (2012) (henceforth NDHKM). We uncover that NDHKM relied on a regression model which included a log transformation of variables that are not strictly positive. This led to nonrandom omission of a large proportion of observations. Furthermore, we show that NDHKM’s use of co-integrated regressions is not a suitable empirical strategy for estimating the causal effect of aid on income. Evidence from a Panel VAR model estimated on the dataset of NDHKM, suggests a positive and statistically significant long-run effect of aid on income.Peer reviewe

Aid and income:Another time-series perspective

In a recent article, Nowak-Lehmann, Dreher, Herzer, Klasen, and Martínez-Zarzoso (2012) (henceforth NDHKM) conclude that foreign aid has not had a significant effect on income, based on evidence from panel data potentially covering 131 countries over the period 1960-2006. The present study provides a replication of the empirical results reported by NDHKM. We uncover that NDHKM relied on a regression model that included a log transformation of variables that are not strictly positive. This led to a non-random omission of a large proportion of observations. Furthermore, we show that NDHKM's use of co-integrated regressions is not a suitable empirical strategy for estimating the causal effect of aid on income. Given the nature of the variables and the question under investigation, a Vector Autoregressive (VAR) model can arguably better address the inherent endogeneity problem in the aid-growth relationship. Evidence from a panel VAR model estimated on the dataset of NDHKM, suggests a positive and statistically significant long-run effect of aid on income