DV494 Half Unit
Foundations of Applied Econometrics for Economic Development Policy
This information is for the 2025/26 session.
Course Convenor
Dr Diana Weinhold
Availability
This course is compulsory on the MSc in Development Management (Applied Development Economics), MSc in Development Management (Applied Development Economics) (LSE and Sciences Po) and MSc in Economic Policy for International Development. This course is available on the MSc in Anthropology and Development, MSc in Development Management (Political Economy), MSc in Development Management (Political Economy) (LSE and Sciences Po), MSc in Development Studies, MSc in Environmental Economics and Climate Change, MSc in Health and International Development, MSc in International Development and Humanitarian Emergencies, MSc in Political Economy of Late Development and MSc in Political Science (Political Science and Political Economy). This course is available with permission as an outside option to students on other programmes where regulations permit. This course uses controlled access as part of the course selection process.
Students on the MSc Development Management (ADE) stream, in addition to students on the MSc Development Studies/MSc Health and International Development considering the ADE specialism, will need to attend the Applied Development Economics session on Monday 22 September 2025.
Deadline for application: You should make your request to take ID courses by 12 noon Friday 26 September 2025.
You will be informed of the outcome by 12 noon Monday 29 September 2025.
Students do not need to write a statement to apply for this course.
For queries contact: Intdev.enquiries@lse.ac.uk
DV494 is the required prerequisite for the three ID Economic Development Policy courses, DV490, DV491 and DV492.
The course is designed to be taken in tandem with DV490 in the AT, and/or alone in AT in advance of DV491 and/or DV492 in the WT.
Course content
The purpose of DV494 is to prepare a broad range of students to consume and critically engage with quantitative analysis for international development. Drawing upon applied papers from top academic journals in development economics, political science, political economy, and related disciplines, students will engage with the challenges of causal inference in settings where scarce data, omitted variables, reverse causality, and selection bias must be addressed. We engage with empirical debates from across international development, with examples illustrating how creative quantitative research designs can contribute to our understanding of economic growth, poverty, inequality, cultural and historical processes, gender norms, private sector development, health and education, and government capacity, among other themes.
We begin with an introduction to the philosophy of classical hypothesis testing and multiple regression analysis. We then explore how these tools are used in practice for causal inference in the real world; students will be introduced to a range of research designs, including panel data with fixed effects, difference-in-differences, event studies, instrumental variables, regression discontinuity designs, matching and synthetic controls, and randomized controlled trials. We also briefly explore recent advances in big data, AI and machine learning in development research.
The emphasis of the course is on developing applied skills for sophisticated engagement with frontier quantitative analysis in international development; there are no prerequisites - we focus on teaching students from a broad range of backgrounds. As we teach from the frontier of research in international development there are opportunities for students with backgrounds ranging from little or no statistics to those with degrees in quantitative disciplines to challenge and expand their methodological intuition and skills.
While the primary focus of the course is on learning to read, understand and rigorously consume empirical research, a series of Stata exercises will also provide students with a basic introduction to data management and statistical modelling.
Teaching
10 hours of seminars and 20 hours of lectures in the Autumn Term.
This course has a reading week in Week 6 of Autumn Term.
There will be optional weekly coding Workshops
Formative assessment
A series of weekly problem sets and Stata exercises in the AT will provide formative skill building
Indicative reading
- Angrist, Joshua D., and Jörn-Steffen Pischke. Mastering Metrics: The Path from Cause to Effect. Princeton University Press, 2014.
- Cunningham, Scott. Causal inference: The mixtape. Yale University Press, 2021.
Assessment
Exam (60%), duration: 120 Minutes in the January exam period
Problem sets (40%)
Key facts
Department: International Development
Course Study Period: Autumn Term
Unit value: Half unit
FHEQ Level: Level 7
CEFR Level: Null
Total students 2024/25: 84
Average class size 2024/25: 17
Controlled access 2024/25: YesCourse selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Personal development skills
- Self-management
- Team working
- Problem solving
- Application of information skills
- Communication
- Application of numeracy skills
- Specialist skills