Summer 2023 Fellows: Gabriela Holzer ’25, Kate Li ’25, Lukas Lopez-Jensen ’25, Patricio Ortiz ’25
Development Impact Evaluation (DIME) is a Department of the World Bank’s Development Economics Vice Presidency. DIME’s purpose is to increase the use of impact evaluation (IE) in the design and implementation of public policy and to develop institutional capacity and motivation for evidence-based policy.
DIME aims to overcome the challenge of identifying true cause-and-effect relations in policy programs. By linking researchers to policymakers and feeding results back into policies, DIME fosters systematic use of evidence, which informs adoption, mid-course corrections, and scale-up of policies. Through workshops and clinics with operational staff and government clients, joint research teams, active field coordination, as well as research products such as seminars, papers, and policy briefs, DIME builds capacity while forming a wider community of practice.
With a portfolio of more than 220 impact evaluations, DIME operates across all sectors in about 60 countries spanning the globe. The IEs test a variety of interventions and mechanisms to understand why policy succeeds or fails and how to improve policy design and implementation to obtain better results. By working proactively in collaboration with clients, DIME employs experimental methods to infer causality whenever possible (79% of the portfolio). 17% of DIME IEs utilize non-experimental methods, while 4% use a combination of the two.
Description of the Work
The internship program at DIME combines project-specific experience with training opportunities on survey and data-related topics. DIME’s diverse portfolio offers interns the opportunity to contribute to projects across all development sectors, including agriculture, public sector governance, climate change (energy, environment and water), financial & private sector, human development, entertainment education, transport, trade, gender, and fragility, conflict and violence.
Experience in impact evaluations, working with Stata, R, Python, survey programming (ODK), is desired.