The Fight of the IMF against Corruption in Developing Countries: A Quantitative Assessment of Conditionality Using an Instrumental Variable Approach

The International Monetary Fund (IMF) has become a central player in addressing corruption within developing countries, primarily through anti-corruption conditionalities attached to its financial assistance programs. These conditions emphasise enhancing transparency and accountability, viewed as critical in curbing corrupt practices. Grounded in the principal-agent theory, which frames corruption as a consequence of misaligned incentives between agents (political leaders) and principals (citizens), the IMF's approach aims to realign these incentives. To test the effectiveness of these anti-corruption conditionalities, this study employed a quantitative analysis using an instrumental variable approach to assess their impact on corruption levels across 119 countries from 1997 to 2018. A novel methodology developed by Angin et al. (2024) involving automated text analysis was used to identify and categorise IMF anti-corruption conditions more accurately. The findings indicate that these measures initially lead to increased corruption scores, likely because heightened transparency and accountability have made corrupt practices more visible. This study offers valuable insights into the role of international organisations in promoting good governance and offers policy recommendations for effective implementation strategies.