Publication Date


Date of Final Oral Examination (Defense)


Type of Culminating Activity


Degree Title

Master of Arts in Political Science


Political Science

Major Advisor

Nisha Bellinger, Ph.D.


Michael Allen, Ph.D.


Brian Wampler, Ph.D.


At the turn of the century, while facing significant criticism for the inherent invasiveness of structural conditionality, the frequently high number of conditional requirements attached to loans, and relatively low implementation rates of conditional reforms, the IMF made a series of changes to their conditionality practices to streamline back to their core organizational mission of macroeconomic stability. The IMF defends its continued use of structural conditions with the institutional transparency and accountability that these conditions seek to impose, thereby reducing corruption. IMF structural conditions can however create new opportunities for corrupt linkages to develop and limit the state’s institutional capacity to limit corruption. This study seeks to assess the impact of IMF structural conditionality on corruption within 131 countries between 2000 and 2014. Replicating Stubbs, Reinsberg, Kentikelenis and King’s 2018 methodology, this study implements these scholars’ maximum likelihood estimation with an instrumented variable approach to isolate those structural conditions imposed through IMF lending arrangements to assess their effects on a specific indicator of governance, corruption. The findings indicate structural conditionality does not significantly reduce corruption; this effect is statistically insignificant and not distinguishable from zero. While no broad conclusions can be reached in the setting of statistical insignificance, the IMF’s contention that structural conditionality uniformly abates corruption across borrowers is called into question.