Proposal Description:

Three hundred million of the world’s rural poor suffer from seasonal hunger. Seasonal hunger often occurs between planting and harvest when the demand for agricultural labor falls and the price of food rises. Those affected miss meals for a two- to three-month period, which is especially problematic for young children because poor nutrition for even a short time can limit their development in the long run. A family may increase their income and food security by sending a migrant to work in an urban area, but there may be barriers to migration, such as financial constraints, lack of information about urban job opportunities, or desire to remain with one’s family.
In past work, Professor Mobarak has shown that small cash grants or loans of just $11.50, enough to pay for a migrants travel costs, can help greatly incentivize migration. Such programs were tested in Bangladesh using a Randomized Control Trial (RCT) and shown to be very effective: 57% of families who were offered cash grants sent a migrant, compared to only 36% in the control group. More importantly, overall consumption increased by about 10% in the incentivized groups, while consumption of food increased by an average of 106 calories per person. Finally, the programs were largely sustainable: migrants who were incentivized in prior years were more likely to migrate the following year (47% vs 39%) – even absent an intervention.
Professor Mobarak would like to build on past results. Open questions that remain are: how well can this work be replicated in other countries? Which villagers should be targeted for intervention to best propagate knowledge of migration through social networks? Finally, how effective is this program if it is scaled up so that migrants begin to make up a large percent of the urban work force?
Primary RA responsibilities for this project may include: data cleaning, data analysis, and translating analysis into clear and ordered graphs, tables, etc.

This position is for the Spring 2018 academic semester. Students will work with Professor Mushfiq Mobarak and his research team. RAs demonstrating superior skill and motivation are encouraged to continue expanding their work with Professor Mobarak beyond the Spring semester.

Also copy your application to Meir Brooks (meir.brooks@yale.edu)

Requisite Skills and Qualifications:

Ability to work with STATA at a basic level is highly desirable. A quantitative background, especially in statistics, data analysis or economics, is a strong plus, as is any experience with Randomized Control Trials. Although learning from and collaborating with more senior researchers is an important part of the job, RAs should also be motivated and independent problem solvers.