Prof Valentino Larcinese

This course is available on the MRes/PhD in Political Science, MSc in Comparative Politics, MSc in Conflict Studies, MSc in Political Science and Political Economy, MSc in Public Administration and Government (LSE and Peking University), MSc in Public Policy and Administration and MSc in Regulation. This course is available with permission as an outside option to students on other programmes where regulations permit.

Please note: this course is available to all MSc and MRes students from the Government department. Students from other departments are also welcome but should request permission from the teacher.

A good knowledge of statistics and of the generalized linear model at the level of MY452.

This course provides an introduction to current empirical research in political science with a focus on methods for causal inference. The weekly meetings consist of a mix of lectures and tutorials.The lectures will present the techniques and illustrate their applications by making extensive use of the most up-to-date empirical literature. The tutorials will give feedback on formative work and will provide an opportunity to learn how to apply the methods with the statistical software Stata. After reviewing the rationale for simple OLS estimation, particularly focussing on the conditions for a causal interpretation of the coefficients, the course will cover instrumental variables, panel data, differences-in-differences, regression discontinuity and several applications to political science. Students will be stimulated to think in experimental terms and the main theme will be how to replicate or get close to the experimental ideal of natural sciences by using non-experimental observational data.

This course is delivered through a minimum of 30 hours of lectures and tutorials in the Lent Term. Some or all of this teaching will be delivered through a combination of online and on-campus lectures and tutorials. There will be a reading week in Week 6 of Lent Term.

There will be two pieces of formative work to be submitted to the lecturer.

Most readings will be journal articles. The main references for the methods will be:

Thad Dunning: Natural experiments in the social sciences, Cambridge University Press 2012

Angrist & Pischke: Mostly Harmless Econometrics, Princeton University Press 2009.

Stock & Watson: Introduction to Econometrics, Pearson 2007 (Second edition)

Online assessment (40%, duration: 7 days) in the ST.
Essay (50%) in the ST Week 1.
Presentation (10%) in the LT Week 11.

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.