By Emily Miller
When policymakers tackle poverty alleviation, they often overlook a critical element: migration. The movement of people is often left out of standard economic models, because it is hard to collect data on migrants and migration patterns. But understanding why people move or don’t move matters for the success of development policies, says Melanie Morten. The SCID Faculty Affiliate and Stanford Assistant Professor of Economics is devoted to mathematically modeling migration.
One striking fact about many low-income countries is the large difference in wages between urban and rural areas. On average, labor productivity in cities is at least double labor productivity in the countryside. This leads to a clear policy challenge: should governments use resources to improve productivity in low-income parts of the country, or should they encourage migration to places that have better jobs? Understanding both the decision to migrate as well as understanding the efficacy of policies to address regional inequality first involves understanding how people make the decision to move.
When governments address income inequality between rural and urban areas, they often rely on "place-based" policies to specifically target the residents of a poor area. Morten uses these policies to illustrate the policy implications of people’s migration decisions.
For example, Brazil's social housing policy Minha Casa, Minha Vida subsidizes mortgages to make it possible for low-income people to live in cities and reap the benefits of higher urban wages. In a recent working paper, Morten sheds light on how connectivity to roads and highways affects a person’s ability to migrate, and therefore their ability to benefit from the housing policy.
For those living in remote areas not easily accessed by major roads networks, their cost of migrating to another city is much higher than those coming from another city served by major roads. As a result, Morten finds that Brazil's mortgage assistance policy stands to disproportionately benefit people who already live close to urban areas. However, it may not impact low-income populations in more remote rural areas – potentially those most in need of higher wages.
In India, the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) seeks to make rural areas more livable for the poor by guaranteeing 100 days of work per year for rural households. Temporary jobs on public works projects can compensate for lost income from a bad harvest. But MGNREGA isn’t the only option for Indian farmers facing a poor harvest. In research building on her PhD dissertation at Yale, Morten shows that farmers often seek short-term work in urban areas as a stopgap measure to keep incomes up. One fifth of rural households currently receive income from a family member who has temporarily moved elsewhere for work. Unsurprisingly then when income (employment) is provided through MGNREGA, temporary urban migration falls. Morten explains that while MGNREGA has been touted as a welfare policy success story, after accounting for the ways rural household had previously managed to keep incomes up through migration or other sharing of family finances, the added benefit from MGNREGA is much smaller.
Understanding why individuals chose to migrate can illuminate the challenges they face and lead to a broader discussion of possible policy solutions. In the case of Brazil’s housing policy, examining migration costs and benefits illuminates the potential bottleneck of transit infrastructure which can undermine the policy’s intentions. Understanding what motivates the migration of Indian farmers can lead to discussions of credit provision or savings accounts – various ways to protect against lost crop income that might be less costly that providing guaranteed employment. By concretely modeling migration decisions, Morten’s work prompts questions for policymakers that can give rise to more effective development strategies.