Reassessing World Bank Conditionality: Beyond Count Measures

 Abstract                                                                                       

Many studies argue that the World Bank grants favourable loan conditions to allies of its powerful principals. These studies typically use the count of conditions as a proxy for how demanding loans are on borrowers, even though some conditions are more difficult to comply with than others. We propose a new operationalization: a measure of conditionality stringency in Bank loans constructed using Latent Semantic Scaling. Using this new measure, we find little evidence of a generalizable influence of powerful principals. Instead, the stringency of loan conditions is associated with bureaucratic assessments of risk. To facilitate future research, we provide a new dataset of World Bank loan condition texts and our measure of text stringency for all loans in the dataset.