Using a panel data set on 103 developing countries, this paper empirically analyses the impact of the European aid flows on quality of governance in aid recipient countries. The analysis employs aggregated Official Development Assistance data as well as disaggregated project-level data. The results show that, while bilateral aid from the largest European donors does not show any impact, multilateral financial assistance from the EU Institutions leads to an improvement in governance indicators. These findings thus suggest that European development assistance can contribute to promoting good governance if aid is allocated at the EU supranational level rather than at the national level of the member states.
Cette étude, en utilisant les données de 103 pays en voie de développement, analyse empiriquement l’impact de l’aide européenne au développement sur la qualité de la gouvernance des pays bénéficiaires. L’étude se base sur des données agrégées de l’aide publique au développement (APD) ainsi que sur des données désagrégées recueillies au niveau des projets. L’étude montre que les projets bilatéraux des plus grands bailleurs européens n’ont aucun impact, tandis que les projets d’aide multilatérale des institutions européennes ménent à une amélioration des indicateurs de bonne gouvernance. Ces résultats suggérent alors que l’aide européenne au développement peut contribuer à la promotion de la bonne gouvernance si elle est attribuée au niveau supranational de l’UE plutôt qu’au niveau national des Etats-membres.
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The figures stem from the EU AID Explorer Website, an official Web tool for aid information operated by the European Commission. euaidexplorer.jrc.ec.europa.eu
See also Booth (2011) for an overall discussion about the role of governance in designing development policy in recent years.
Similarly, Wright and Winters (2010) argue that donors generally do not provide assistance only guided by the recipient-country needs but also for their strategic reasons. However, they also point out that there are differences even within bilateral donors with some countries behaving less strategically, and, especially, over time with some recent evidence suggesting that donors respond to local governance characteristics.
To capture bilateral aid flows, the analysis was also carried out using the sum of aid disbursements from all current EU DAC member states. The corresponding estimation results do not differ qualitatively from those reported below and are available upon request. In particular, the effectiveness of bilateral aid was not affected by the inclusion of further EU national donors.
Molenaers and Nijs (2011) theoretically argue that these instruments might not be properly designed to deliver promised outcomes.
An alternative data source that offers similar measurements of governance is the International Country Risk Guide (ICRG) database. Provided by a private company – Political Risk Service Group – the ICRG indicators are based only on expert assessments and lack transparency in their construction. Moreover, they are among the primary sources used in building the WGI measurements. For example, the ICRG indicators ‘corruption’, ‘bureaucratic quality’ and ‘law and order’ are included in the WGI measurements of ‘control of corruption’, ‘regulatory quality’ and ‘rule of law’, respectively.
Potential EU candidates also include Kosovo, and the other official EU candidate is Turkey, which is excluded from the sample as being an OECD country since 1961. Moreover, the IPA comprises more components than the above mentioned assistance. Yet, while only official EU candidates are eligible for all IPA measures, potential candidates are only eligible to benefit from financial assistance for transition and institution building and European cross-border cooperation. For more information on IPA, see European Council (2006).
System-GMM is basically the augmented version of the Arelano and Bond (1991) ‘difference GMM’ estimator, which, in our case, would only estimate the second equation using the lagged levels of the regressors as instruments for the first-differenced regressors. By introducing an additional set of ‘internal instruments’, system-GMM leads to more efficient estimators compared with ‘difference GMM’ approach.
If there are three observation periods in the sample, system GMM generates two instruments for each endogenous variable: one lagged value in levels to instrument the first-difference, and one lagged first-difference variable to instrument the level of the corresponding variable (for example, ΔGovernance i3 is instrumented by Governance i1, and Governance i3 is instrumented by ΔGovernance i2.) However, as the time dimension of the sample increases, the number of instruments rises exponentially resulting in an over-fitting of endogenous variables and thus imprecise estimation of the moment conditions. As a consequence, this instrument proliferation can cause biased estimators and specification tests (Roodman, 2009b).
I use the two-step robust estimator that applies the Windmeijers (2005) finite-sample correction for the two-step covariance matrix.
Burundi, Guinea-Bissau, Mauritania account for the largest observations of multirat_aid in the sample and belong to the group of the ACP countries.
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The research was made possible by support from an EU FP7 ANTICORRP project (Grant agreement no: 290529) at the Hertie School of Governance.
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Dadasov, R. European Aid and Governance: Does the Source Matter?. Eur J Dev Res 29, 269–288 (2017). https://doi.org/10.1057/ejdr.2016.16
- European development assistance
- EU institutions
- bilateral and multilateral foreign aid
- good governance
- dynamic panel estimations