Feminist work on global human trafficking has highlighted the conceptual difficulty of differentiating between trafficking and migration. This paper uses a cross-country UN dataset on human trafficking to empirically evaluate the socio-economic characteristics of high trafficking origin countries and compare them to patterns that have emerged in the literature on migration. In particular, we ask how and how much per capita income and gender inequality matter in shaping patterns of human trafficking origin. Ordinal logit regressions corrected for sample selection bias tell us that trafficking has an inverse-U shaped relationship with income per capita, and, controlling for income, is more likely in countries with higher shares of female to male income. These results suggest strong parallels between patterns of trafficking and migration and lead us to believe that trafficking cannot be addressed without addressing the drivers of migration