Development Economics

Course goals

At the end of this course, the student is able to:

• Analyse pressing development problems by applying state-of-the-art theories and empirical methods from the frontier of development economics;
• Critically evaluate causal-inference designs, such as randomised controlled trials, difference-in-differences, regression discontinuity, and instrumental variables — as deployed in leading development papers;
• Synthesise theory and evidence across thematic areas and connect them to current policy debates;
• Write a well-structured academic essay on a development economics problem, demonstrating command of theory, empirical evidence, and data-analytical reasoning;
• Critically assess the work of peers and academic researchers in a rigorous and constructive scholarly manner.

Content

Extreme poverty reduction - an important achievements of the last three decades - has stalled. Climate risks are increasing and affecting those who are least able to adapt most. Conflict is spreading, and can reverse years of development gains. The global trade integration that once powered growth in lower-income countries is fraying. And structural inequalities - in income, in health, in education, in who gets to participate in economic life - persist in ways that neither markets nor governments have yet managed to resolve.

This course places you at the frontier of these debates. You will learn why people stay poor - and what it takes to break the cycle. You will examine how economies transform, whether skipping industrialisation and going straight to services can sustain growth, and why firms in low-income countries are so unproductive. You will study what conflict costs, how gender norms constrain billions of people, whether cash transfers change lives, and what poverty does to the mind. And you will ask how we know. Because evaluating the evidence is as important as knowing the results.

What makes this moment especially exciting is how much the data toolkit has changed. A credibility revolution has transformed how development economists answer causal questions - through randomised evaluations, regression discontinuity designs, and instrumental variables that turn historical accidents into natural experiments. At the same time, an explosion of new data sources - satellite imagery, mobile phone records, large administrative datasets - has made it possible to measure poverty, migration, and behaviour at a scale and precision that was unimaginable a decade ago.

Course content

The course is structured around eight thematic modules, the majority anchored by chapters from the forthcoming Handbook of Development Economics, Volume 6 (eds. Dupas, Goldberg & Pande, 2026). The handbook is supplemented with additional seminal and recent papers, and connects to broader theoretical and empirical debates.

The Methods Thread: How Do We Know? Running through all eight modules is a methods thread on the credibility revolution in development economics. You will examine how the field moved from cross-sectional comparisons to randomised evaluations (RCTs), regression discontinuity designs, and instrumental variables that exploit historical accidents. By the end of the course, you will be able to assess not just what a study finds, but whether to believe it — a skill that is equally valuable in academia, policy, and the private sector.

The Data Thread: New Tools for Old Questions A second thread connects directly to your Economics and Data Analysis programme. Development economics has been transformed by new data sources: satellite imagery to measure poverty and deforestation; mobile phone records to map migration and social networks; large administrative datasets to evaluate policy at scale. Problem sets in this course will give you hands-on experience applying these tools — in R or Python — to real development questions.