GV324 Half Unit
Applied Quantitative Methods for Political Science
This information is for the 2019/20 session.
Prof Valentino Larcinese CBG.3.02
This course is available on the BSc in Government, BSc in Government and Economics, BSc in Government and History, BSc in Philosophy, Politics and Economics, BSc in Politics, BSc in Politics and Economics, BSc in Politics and History, BSc in Politics and International Relations and BSc in Politics and Philosophy. This course is available as an outside option to students on other programmes where regulations permit and to General Course students.
This course will be freely available to students with the required background
Students must have completed Quantitative Methods (Mathematics) (MA107) and Quantitative Methods (Statistics) (ST107).
This course provides an introduction to the most commonly used methods for causal inference in the social sciences using observational data. It covers simple and multiple regression (particularly focussing on the conditions for a causal interpretation of the coefficients), matching, panel data, diff-in-diff, instrumental variables, regression discontinuity. The course will prioritize the practical understanding and application of the methods rather than their statistical foundations. Applications will be selected from existing research literature.
20 hours of lectures and 9 hours of classes in the LT.
Teaching will consist of 10 2-hour lectures during the LT and 9 1-hour classes. Classes will be conducted in a computer lab.
Students will be expected to produce 1 problem sets and 1 case study in the LT.
Stock & Watson: "Introduction to Econometrics", Pearson International (various editions, all equally valid)
Dunning: "Natural experiments in the social sciences", CUP 2012
Angrist & Pischke: "Mastering metrics", Princeton University Press 2015
Exam (100%, duration: 2 hours, reading time: 15 minutes) in the summer exam period.
Total students 2018/19: Unavailable
Average class size 2018/19: Unavailable
Capped 2018/19: No
Value: Half Unit
Personal development skills
- Team working
- Problem solving
- Application of information skills
- Application of numeracy skills