Every year, students at McCourt School’s Master in International Development Policy (MIDP) work with a client to produce an applied empirical report which answers a policy-relevant question. Past clients include: ARK, iDE, IFPRI, Mercy Corps, the Tony Blair Africa Governance Initiative, Twaweza, Peloria, USAID, the Millennium Challenge Corporation (MCC), and multiple different units at the World Bank. I have advised students through this process since 2015.
I provide some examples of previous projects below (including links to the reports and a policy brief summarizing the results).
The Drivers and Returns to Migration — Mercy Corps
Using panel data from DRC, Pakistan, and Sri Lanka, students examined the effects of exogenous shocks on migration likelihood. Crop/livestock disease had the most significant effect, increasing the likelihood of migration by 11.2 percentage points.
The 2015 Gorkha Earthquake in Nepal — World Bank
Students analyzed exposure, vulnerability, and resilience patterns following the 2015 earthquake. Poorer households experienced proportionally greater asset losses and relied more on expenditure reduction strategies.
Inequality of Opportunity in Ethiopia — World Bank
Students examined trends in service access inequality between 2011-2016. Rural status is by far the largest driver of inequality, compared to income or education.
Can Sanitation Marketing Improve Latrine Usage and Reduce Incidence of Diarrhea? — iDE (Cambodia)
Students evaluated the impact of sanitation marketing in Cambodia. Latrine coverage increased by 17.8 percentage points while diarrhea decreased by 5.8 percentage points.
Household Resilience to Conflict in Nigeria — Mercy Corps
Using a triple-difference strategy, students examined determinants of resilience. Villages with higher social capital effectively mitigated negative conflict impacts on child malnutrition.
Ebola's Impact on Labor Markets in Sierra Leone — World Bank
Students studied employment effects in regions with varying Ebola exposure. Farming sector employment declined in heavily exposed regions, partially offset by increased non-formal self-employment.
Violence Prediction in Iraq — Mercy Corps
Students used machine learning to analyze violence predictors. Voting behavior and tribal chief connections emerged as the strongest predictive factors.
Private School Vouchers in India — ARK
Students evaluated a randomized low-fee private school voucher program in New Delhi. The program showed a negative impact on Hindi learning but a positive impact on English outcomes.