Volume, Risk, Complexity: What Makes Development Finance Projects Succeed or Fail? - Yota Eilers; Jochen Kluve; Jörg Langbein; Lennart Reiners (Institute of Labor Economics (IZA), 2023)
In 2022, governments around the world committed USD 211 bn. to official development assistance. Despite these high contributions, systematic assessments of the determinants of success - or failure - of development aid projects remain limited, particularly for bilateral development aid. This paper provides such a systematic, quantitative analysis: we construct a unique database covering 5,608 evaluation results - success ratings - for bilateral development aid projects financed through one of the biggest global donors, KfW Development Bank. Detailed data on project characteristics allow us to link success ratings to five clusters of key explanatory factors along the entire project life-cyle and context: (a) In terms of project financing, we find a statistically significant positive association between the financial budget volume of the project and its success ratings, ceteris paribus. Second, concerning the (b) project structure, the type of project partner - government, private sector, multilateral organizations - shows no significant association with project success, suggesting that project implementation works equally well with different partners. (c) Project complexity as measured by both technical complexity and longer implementation duration exerts a negative influence on success ratings. Regarding (d) project risks, a highly relevant and significant predictor for less successful projects is the share of ex-ante identified risks that eventually materialized - suggesting that project designs correctly identify the relevant risks in advance, but are not able to mitigate (all of) them during execution. Finally, concerning (e) the project context there is some indication that higher GDP growth rates are positively associated with project success.
Keywords: C40; F35; O10; O19; 330; development finance; OECD DAC evaluation criteria; meta analysis