Instructor: Jacob Edenhofer
Institution: University of Oxford – Nuffield College
Term: Trinity Term 2025
Contact: [email protected]
This course offers a formal treatment of foundational models in political economy, focusing especially on democratic institutions, such as elections, political parties, and interest groups. It aims to both deepen theoretical understanding and explore the real-world implications of these models. The course is designed for students with little prior exposure to formal theory.
.
├── 01 Readings/ # Required and optional readings by week
├── 02 Slides/ # Weekly lecture slides
├── 03 Simulations/ # Jupyter notebooks and R scripts for simulations and visualizations
├── 04 Assignments/ # Weekly assignments and solution sets
│ └── Solutions/ # Reference solutions (in both R and Python)
├── Syllabus_TT2025.pdf # Full course syllabus
├── README.md # This file
| Week | Topic | Key Models & Themes |
|---|---|---|
| 01 | Electoral Accountability | Voter control, selection vs. sanctioning |
| 02 | Party Competition | Formal justifications for parties, Downsian model of party competition and extensions |
| 03 | Distributive Politics and the effects of Electoral Rules | Core vs. swing voter debate and formal models of electoral rules |
| 04 | Interest Groups and Lobbying | Formal models of lobbying and interest group influence |
| 05 | Bonus: Democratic Backsliding | Strategic erosion of democratic norms |
📌 Formative Assessment:
Students can choose between weekly essays or sets of exercises based on the week’s model.
- Readings: Navigate to
01 Readings/WeekXto access all PDFs for the corresponding week. - Slides: All lecture slides are in
02 Slides/. - Simulations: Go to
03 Simulations/WeekXto run notebooks illustrating models with real or simulated data. Figures are stored in theFigures/subfolder. - Assignments: Each week includes an assignment PDF and solution materials (Python/R) under
04 Assignments/.
- No strict prerequisites, but familiarity with game theory and formal political theory is helpful.
- You may need:
- Python (preferably with
Jupyter) - R
- Basic linear algebra, probability, and calculus
- Python (preferably with