This article argues that international organizations influence domestic policy not only directly, but also indirectly: in addition to setting international best practices, they affect how domestic institutions set practices of their own. To test this argument, I use unsupervised machine learning to identify the effect of IMF conditionalities on natural resource policy in middle and lower income countries. Using a novel dataset of all laws creating and regulating natural resource funds between 1980 and 2019, I find that governments are more likely to pass such laws when they have outstanding IMF loans, and the content of these laws tends to mirror the content of loan agreements. This has implications not only for the transparency and accountability of the extractive sector, but also for the long-term impact of natural resource wealth on public budgets and social welfare. Ultimately, the study of natural resource policy can help us understand how international organizations have a latent potential to influence the domestic agenda.
São Tomé and Príncipe’s 2000 oil law