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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, an...
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... first (and typically main) aim of any meta-analysis is to combine the available empirical evidence so as to establish whether the impact of an intervention is different from zero or not. Accordingly, in Table 1 we present the combined estimates of the impact of aid on growth (and the associated confidence intervals) from fixed and random effects meta analysis. Both suggest a positive and significant effect of aid on growth (0.082 and 0.098 respectively) when the empirical evidence from the 68 studies is combined. ...
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... reported in Table 1 suggests. 14 The presence of heterogeneity is also clearly confirmed in graphical inspection of the Galbraith plot attached in the appendix. ...
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... back to the overall effect of aid reported in Table 1, the weighted average effect of aid on growth from the 68 studies is positive and statistically significant with a magnitude of 0.098 in the random effect meta analysis. On the other hand, the weighted average effect reported in DP08 is 0.08 which is similar to the fixed effect estimate reported in Table 1. ...
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... back to the overall effect of aid reported in Table 1, the weighted average effect of aid on growth from the 68 studies is positive and statistically significant with a magnitude of 0.098 in the random effect meta analysis. On the other hand, the weighted average effect reported in DP08 is 0.08 which is similar to the fixed effect estimate reported in Table 1. Note from Table 1 that the DP08 weighted average does not fall in our 95 per cent confidence interval which indicates that we can reject their 0.08 estimate at 5 per cent level of significance. ...
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... the other hand, the weighted average effect reported in DP08 is 0.08 which is similar to the fixed effect estimate reported in Table 1. Note from Table 1 that the DP08 weighted average does not fall in our 95 per cent confidence interval which indicates that we can reject their 0.08 estimate at 5 per cent level of significance. ...
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... magnitude is much higher than the estimate found for papers that include at least one of the interaction terms. Moreover, this estimate is also higher than the one reported in Table 1 where the non-linearity issues are ignored. ...
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... we expand the FAT-MRA model by including all the 50 moderator variables they identified. The result is depicted in Table A1 in the appendix, and it can be seen that the magnitude of the precision coefficient improves and becomes significant in two of the cases, though it fails to be significant in the last column. ...
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... suggests that once the moderator variables (study characteristics) are controlled for then there is no publication bias. However, most of the variables included in the multivariate regression reported in Table A1 are statistically insignificant. There is, in other words, a trade-off here between including these variables in order to explain heterogeneity versus potential multicolleniarity and loss of degrees of freedom. ...
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Citations
... Some of the studies are related to agriculture but are different from the focus area of our study. These include the impact of genetically modified (GM) crops [48]; farm-level cost and benefit analysis of GM crops [49]; economic and agronomic impact of commercialized genetically modified crops [50]; impact of agricultural subsidies on farm technological efficiency [51]; impact of microfinance interventions [52]; an efficiency and productivity analysis of Pakistan's farm sector [53]; assessing the returns to water harvesting [54]; willingness to pay for reducing pesticide risk exposure [55]; and nutrient management in African sorghum cropping systems and an assessment of yields and profitability [56]. 1 Applications of meta-analyses in diverse areas include the effects of immigration on wages [57]; income and calorie intake [58]; income inequality and economic growth [59]; the impact of technical barriers to trade [60]; effect of aid on economic growth [61]; energy consumption and economic growth [62]; effect of currency unions on trade [63]; price and income elasticity of demand for meat [64,65]; price and income elasticity of demand for alcohol [66]; income elasticity of demand for cigarettes [67]; assessing the impact of interventions in fisheries' co-management in developing countries [68]; exchange rate volatility and trade [69]; and debt and economic growth [70]. Recently, Ogundari and Bolranwa [38,71] used MRA to provide insights into agricultural extension services' impact. ...
A large body of researches have widely examined the impact of adopting improved agricultural practices and technologies on general welfare of smallholder farmers. The results of deep literature review show that varies agricultural technologies have significant impacts on different welfare measures identified in the primary studies. However, the estimated effects of technology adoption differ among studies. The current study presents a meta-analysis of empirical estimates using a sample of 52 studies that investigated the impact of improved agricultural technologies in Africa on three key sets of outcome variables: output or expenditure, food security, and poverty. The study also conducted tests for publication bias to see if researchers tend to report results in similar or different ways for the same outcome variable. The findings the study shed light on the ways of identifying potential factors explaining the differences in the effects of estimated technology adoption. Results of the meta-regression analysis revealed that differences in the reported impact of technologies is explained by factors like data type, model specification, sample size, region of the study, and journal type. It was also observed that no publication bias in the studies reviewed for the effect size measures of output (expenditure) and poverty models, but in the food security model there is some evidence of publication bias. One of the core implications of the current study is that, based on the sensitivity of effect sizes to study attributes (i.e. data type, econometric methods, sample size, region of the study, and journal type), interested researchers and academicians need to pay attention to these attributes to provide more reliable estimates for policy interventions. We believe this study provides information useful to interested decision-makers in designing policy intervention measures that could encourage the adoption of improved agricultural practices and technologies in the African context. Finally, the study also highlighted future research directions.
... In similar results, Collier & Dollar (2002) reinvestigated the later results by Burnside & Dollar (2000) and found that aid effectiveness depends upon the policy environment and aid is subject to diminishing marginal returns. These findings are also consistent with the studies of (Mekasha & Tarp, 2013;Tan, 2009;Nwaogu & Ryan, 2015;Sothan 2018;Sethi et al., 2019). ...
... For instance, Mekasha & Tarp (2013) used data from 68 aid-growth studies from 1970 to 2004 to conduct a meta-analysis. In their research, they discovered that foreign aid has a significant effect on growth. ...
This paper investigates the impact of Aid for Trade inflows on economic growth in developing countries, and whether this impact is dependent on the institutional quality of these countries. The empirical analysis covers 75 recipient countries over the 2009- 2018 period. This study applies the Quantile Regression approach. The empirical findings suggested the significant impact of the aggregate Aid for Trade inflows over the full sample, precisely, the low-income recipients. In terms of its categories, Aid for Trade for productive capacity building generates the largest positive impact, followed by Aid for Trade for policy and regulations, while Aid for Trade for economic infrastructure was observed to have the weakest positive effect. Furthermore, Aid for Trade interaction with institutional variables was found to be negative. However, these coefficients appear to converge toward positive in the case of countries with better institutional quality (high-income recipients).
... The problem of regional inequality and the role of ODA The regional dispersion and distribution of aid is a long-standing topic of academic and practical relevance. A considerable portion of the economics (Mekasha and Tarp 2013;Sumner and Glennie 2015) and politico-economic literature (Bueno de Mesquita and Smith 2009;Neumayer 2003) has traditionally focused on the international distribution of aid. Recently, the better availability of geocoded information on ODA has allowed academics also to investigate the internal distribution of ODA within countries (Bluhm et al 2018;Briggs 2017). ...
There is a cyclical nature to the dilemmas confronting international donors willing to operate in Myanmar. Brief periods of relative openness led to rapid surges in development assistance, regularly interrupted by long phases of military rule and disengagement by donors. Amidst all this, many predicaments remain. This article engages with one of them: the inequality between regions. How have international donors reacted to the issue of domestic regional inequality? Recent studies suggest that official development assistance (ODA) does not target poor regions very well, but it is not always clear why this is the case. Myanmar's sudden, yet uneven and unequal liberalization from 2011 to 2021 catalyzed huge inflows of ODA, while it also confronted donors with new policy dilemmas. The article shows that aid providers struggle with the problem of rising regional inequality, especially for political reasons. Donor and recipient interests often do not align well on this issue. In the case of Myanmar, donors who press for regional inequality to sit prominently on the agenda might fare less successfully than those who address the issue indirectly. The article concludes that regional inequality and the politics of targeting deserve a more central role in the political economy of ODA. ARTICLE HISTORY
... The effectiveness of foreign aid on growth and development of the recipient economy depends upon the type of aid provided (Maruta et al., 2020;Aljonaid et al., 2022;Kaya et al., 2012). However, a large part of the literature on aideffectiveness has been examined on the basis of aggregate foreign aid (Arndt et al., 2015;Mekasha and Tarp, 2013). As a result, the effect of sector-specific aid on aggregate economic growth and development has not been adequately analysed. ...
... The debate in the aid-growth literature documents five generations of previous studies . While one group of studies show optimistic results (Sethi et al., 2019;Mekasha and Tarp, 2019;Civelli et al., 2018;Juselius et al., 2017;Galiani et al., 2017;Arndt et al., 2015;Mekasha and Tarp, 2013;Booth, 2011), the other group refers to several problems related to foreign aid, like the micro-macro paradox and the Dutch-disease effects (Asongu and Nwachukwu, 2016;Subramanian, 2008, 2011;Mosley, 1986). Dalgaard and Hansen (2015) estimated the average rate of return on aid-financed projects and investments using a correlated random coefficients model for estimating average returns. ...
The study analyses the effectiveness of aggregate as well as sectoral foreign aid on growth and structural transformation for 32 sub-Saharan African (SSA) countries over the period from 2002 to 2019. For this purpose, a structural transformation index (STI) has been constructed using the value-added and employment shares of the economy. There is a lack of studies in the aid effectiveness literature that examine the effects of sectoral aid on overall growth and development of the economy. Comparing the effectiveness of different types of aid on growth and structural transformation is a novel approach. In this analysis, we also take into account the roles of institutional quality and human capital on aid effectiveness. To this end, we have used Driscoll–Kraay Fixed-Effect estimators, Fixed-Effects Panel Threshold regression and Method of Moments Quantile regression to analyse the effectiveness of aggregate and sectoral foreign aid. Our estimation techniques are robust to cross-sectional dependence and slope heterogeneity. We find that both agricultural and social-sector aid have positive significant effects on growth but negative significant effect on structural transformation. This suggests that foreign aid should be increased in these sectors, conditioned by the level of institutional quality. Human capital is found to increase the effectiveness of foreign aid. Aid to economic infrastructure is the only type of aid which is found to increase structural transformation significantly. This study helps in designing aid allocation strategies, so as to promote both growth and structural transformation in the SSA countries.
... The nexus between foreign aid and growth has also been mixed and inconclusive, and the reasons are not far-fetched from that accounting for the disparity in the relationship between external debt and growth. Prominent past empirical studies which found a positive relationship between foreign aid and economic growth include: (Asteriou, 2009;Chowdhury & Das, 2011;Clemens et al., 2012;Fashina et al., 2018;Gomanee et al., 2005;Hussen & Lee, 2020;Kitessa, 2018;Mekasha & Tarp, 2013;Museru et al., 2014;Nwaogu & Ryan, 2015). Contrary to these findings, studies such as (Ali & Isse, 2005;Appiah-Otoo et al., 2022;Boateng et al., 2021;Fatima, 2014;Feeny, 2005;Khan & Ahmed, 2007;Kourtellos et al., 2007;Liu et al., 2014) also reveal that foreign aid negatively affects economic growth and development in developing countries. ...
Over recent years, the Ghanaian economy has struggled to find its feet on the ground despite rising public debt and unending inflows of foreign aid. Against this backdrop, this study employs the Vector Error Correction Model (VECM) estimation technique on data from 1970 to 2020 to test the usefulness of the debt overhang hypothesis and the dependency theory in the special case of Ghana. The results confirm evidence of the debt overhang hypothesis and the center-periphery wisdom of the dependency theory in Ghana. The findings depict that an increase in external debt stock and total debt service on external debt have both short and long-run growth-limiting effects on the Ghanaian economy. Similarly, foreign aid catalyzes growth only in the short run and later suppresses rather than stimulates economic growth in Ghana over the long run. The study recommends that harnessing domestic resources, maintaining fiscal discipline by cutting down unproductive expenditures, enhancing an effective tax system, and promoting institutional capabilities to counteract corruption and openness to trade are better ways to fast-track growth and development in Ghana.
... Quite a number of studies in the growth literature have taken a broader look at aid effectiveness in the developing economies without decomposing aid flows (Dalgaard & Hansen, 2017;Mekasha & Tarp, 2013;Mascagni, 2016;Elayah, 2016;Addison, Morrissey & Tarp, 2017). However, disintegrating aid flows into grants and concessional loans, Sawada, Kohama, and Kono (2004) found that, on average, aid had no effect on growth irrespective of recipient policies, nor did grants. ...
This study investigates the effects of aid grants on inclusive growth in 37 Sub-Saharan African countries for the period 1984-2018. Grant aid is decomposed into aid grants and technical cooperation grants. Two inclusive growth indicators are used namely: gross domestic product (GDP) per capita growth and unemployment rate. The dynamic panel autoregressive distributed lag (ARDL) approach which is employed comprises three different estimators; the pooled mean group (PMG), mean group (MG), and dynamic fixed effect (DFE). The Hausman diagnostics were used to assess the efficiency and consistency of the estimators. Based on the PMG estimator, our findings show that aid grants and technical cooperation grants exert a positive influence on GDP per capita growth in the long-run. However, while the observed influence of aid grants is found to be significant, technical cooperation grants display insignificant effects. In the short run, however, the PMG estimates show that aid grants and technical cooperation grants have negative and insignificant effects on GDP per capita growth. On the other hand, results based the DFE estimators reveal that neither of the aid grants has influenced the unemployment rate positively in the short-run. However, whereas aid grants contribute significantly to the reduction of the unemployment rate in the long run, technical cooperation grants do not. This study complements the attendant literature by assessing how aid grants versus technical cooperation grants affect inclusive growth. The findings are relevant to international policy coordination for the attainment of sustainable development goals.
... Quite a number of studies in the growth literature have taken a broader look at aid effectiveness in the developing economies without decomposing aid flows (Dalgaard & Hansen, 2017;Mekasha & Tarp, 2013;Mascagni, 2016;Elayah, 2016;Addison, Morrissey & Tarp, 2017). However, disintegrating aid flows into grants and concessional loans, Sawada, Kohama, and Kono (2004) found that, on average, aid had no effect on growth irrespective of recipient policies, nor did grants. ...
This study investigates the effects of aid grants on inclusive growth in 37 Sub-Saharan African countries for the period 1984-2018. Grant aid is decomposed into aid grants and technical cooperation grants. Two inclusive growth indicators are used namely: gross domestic product (GDP) per capita growth and unemployment rate. The dynamic panel autoregressive distributed lag (ARDL) approach which is employed comprises three different estimators; the pooled mean group (PMG), mean group (MG), and dynamic fixed effect (DFE). The Hausman diagnostics were used to assess the efficiency and consistency of the estimators. Based on the PMG estimator, our findings show that aid grants and technical cooperation grants exert a positive influence on GDP per capita growth in the long-run. However, while the observed influence of aid grants is found to be significant, technical cooperation grants display insignificant effects. In the short run, however, the PMG estimates show that aid grants and technical cooperation grants have negative and insignificant effects on GDP per capita growth. On the other hand, results based the DFE estimators reveal that neither of the aid grants has influenced the unemployment rate positively in the short-run. However, whereas aid grants contribute significantly to the reduction of the unemployment rate in the long run, technical cooperation grants do not. This study complements the attendant literature by assessing how aid grants versus technical cooperation grants affect inclusive growth. The findings are relevant to international policy coordination for the attainment of sustainable development goals.
... (iii) Those who argue that aid unconditionally benefits economies. For example, the meta-analysis study carried out Mekasha and Tarp (2013) shows that the significant effect of aid on economic growth is genuine, and not as a result of publication selection. Tarp (2010, 2015) claim that aid has a statistically positive long-run impact on economic growth and thus serves as an important means of enhancing development in poor nations. ...
Sustained investment is required for economic growth. Investment however often experiences severe volatility in poor countries, making spending plans difficult to formulate, and diminishing growth potentials. Foreign aid serves as an important source of complementary financing for sustained investment. This paper thus studies the effect of aid inflows on total investment volatility in 19 heavily indebted poor sub-Saharan African countries over the period 1980–2018. Employing the cross-sectionally augmented distributed lag (CS-DL) estimation technique for long-run coefficients in dynamic heterogeneous panels with cross-sectional dependence along with bootstrap panel causality testing, we show that aid has an inverse relationship with investment volatility. We thus conclude that aid can be viewed as a dampening factor for investment volatility in poor countries. We also show that the ability of sudden reductions in aid inflows to trigger investment volatility is bigger than the ability of sudden increases in aid inflows to lower investment volatility.
... In response to the paper of Doucouliagos and Paldam (2013), the analyses of Mekasha and Tarp (2013), and Dalgaard and Hansen (2017) contradict the results of the existing meta-analyses by demonstrating that there was no publication bias and that the aid was generally effective. These meta-analyses, whose aim was to identify once and for all the impact of aid on the growth of developing countries, simply followed in the footsteps of existing analyses by continuing to fuel the debate and uncertainty around aid effectiveness. ...
This paper analyses threshold effects and transmission Channels of foreign aid on economic growth of WAEMU countries using the World Bank, the International Monetary Fund and the International Country Risk Guide databases to cover the period spanning from 1980 to 2018. After applying endogenous threshold approach to determine aid threshold above which its affects growth and estimate its long-term effects, Pagan’s Residual-Generated Regressors method was used to identify channels that can modulate effects of aid on growth. Evidences strongly support the view that the relationship between aid and economic growth is non-linear with a threshold that lies between 12.37 and 14.08% of GDP. Above these values, the marginal effect of aid is 2.1%. Moreover, results indicate that only investment seems to be a potential channel through which aid would affect growth. Thus, aid within the WAEMU countries is beneficial. Its content and use should be the main concern of donors and policy-makers.
... Using extensive estimates of the effectiveness of foreign aid, Doucouliagos and Paldam (2008, 2010 put forth that foreign aid is generally ineffective based on their evidence. On the other hand, Mekasha and Tarp (2013) provided that aid has a positive and genuinely significant effect on growth. Evidently, there is no consensus on the subject. ...
This paper investigates the macroeconomic determinants affecting consumption in Sub-Saharan Africa (SSA) using panel data from 2005 to 2018. Fixed effects models and dynamic fixed effects models are developed and analysed. The first model includes panel data for 25 SSA countries, considering consumption, foreign aid, foreign direct investment, international trade, and inflation. The second model incorporates a monetary policy element by adding money market interest rate. From the models derived, the paper reveals an empirical relationship between international trade and consumption, with trade having a negative effect on consumption which points to a different distribution than is expected. The dynamic fixed effects models respectively establish that past consumption has an effect on present consumption and that monetary policy through interest rate is negatively correlated with consumption. The significance of the other determinants is not proven, which could serve as meaningful information to policy makers when deciding about what really matters.
