The relationship between migration and foreign ODA has not been understudied. The existing literature suggests that aid’s capacity to deter migration is small at best, and even shows that programs in formerly-poor countries have led to an increase in emigration. One way scholars look at the aid-migration link is through income and budgetary constraint effects. The income channel suggests that higher incomes, through developmental aid, will reduce emigration, since the opportunity cost of moving increases. The budgetary constraint channel builds off the fact that migration is costly and increased wealth from aid would decrease the relative cost of migrating and will encourage movement. Especially because many poor families view migration as an investment in their futures and an insurance policy against unexpected economic events at home and decrease in migration costs would make migration easier (Clemens and Postel 2018). Others point to a network effect resulting from bilateral aid relations, where the existence of aid decreases the information cost about potential destinations—increasing migration to developed countries (Barthelemy et al. 2009). Studies like these, however, examine this relationship at an aggregate level – lumping all types of aid like humanitarian, social infrastructure, and debt forgiveness together.
The few disaggregated studies have shown a negative relationship between total aid received and migration rates. Studies have focused primarily on the impact of foreign health aid on the emigration rates of physicians (Moullan 2013) and agricultural aids’ impact on urban and rural emigration (Gamso & Yuldashev 2018). The most recent study on the aid-migration builds on Barthelemy’s gravity model using a disaggregated approach incorporating economic and social infrastructure ODA spending. The results point to “a robust negative relationship between aggregate aid received and emigration rates, which can be attributed to the dominance of the public-services channel over the budgetary-constraint channel” (Lanati & Thiele 2018). Using the example of infrastructure aid, they explain the public services channel simply: better roads from ODA yield a positive externality of more foreign direct investment. As firms can use the roads for commercial purposes, more jobs can be created. This is evidence that local services are an important factor in developing migration decisions – even more than household wealth.
Based on these studies, there seems to be more to the story than what studies on aggregated development aid data and migration flow show. My analysis will examine the relationship between development aid and migration rates, as an extension of Lanati and Thiele’s research. This will include ODA categories: Humanitarian Aid and Production Aid in addition to Social and Economic Infrastructure and Services from Lanati and Thiele’s model. I also include subcategories of each category such as Education and Water Supply. The Action related to Debt, Program, Multisector and Other aid categories are left out, because these types of aid are case-by-case and difficult to incorporate such categories and interpret their results through the lens of my research question. This research aims to achieve greater clarity on how different types of developmental aid effect recipient countries’ migration flows. I will be using an approach similar to Lanati and Thiele’s gravity model to do my analysis.