Dr G Padro i Miquel, R521 and Dr D Sturm, R429.

This course is compulsory for the first year of the MPA Public and Economic Policy/MPA Public Policy and Management/MPA European Public and Economic Policy and MPA International Development. It is an alternate compulsory core course for students on the MSc Political Science and Political Economy and is an option course for other graduate students with the permission of the course lecturer.

The course has no formal pre-requisites. A familiarity with basic statistical concepts and basic calculus are very useful. These topics are reviewed during the pre-sessional course of the MPA programme (MI402). Students not participating in the pre-sessional course need to provide evidence of comparable prior knowledge.

The course introduces students to the quantitative evaluation of public policies with the help of regression based evaluation methods, cost-benefit analysis and computable general equilibrium modelling. The first six weeks of the course introduce students to basic multiple regression analysis including hypothesis testing, modelling of non-linear relationships, and dummy variables. From week 7 of LT the course covers a number of regression based evaluation methods to assess the casual effectiveness of policy interventions. These include the use of randomized experiments, natural or quasi-experiments, panel data, difference-in-differences estimation, instrumental variables, matching and regression discontinuity designs. The final part of the course provides an overview over cost-benefit and cost-effectiveness analysis and an introduction to the use of computable equilibrium models to asses policy interventions.

There are 20 two-hour lectures and 20 one-hour classes. The classes are based on empirical applications, which students have to work through with the statistical package STATA.

Particularly useful textbooks are James Stock & Mark Watson, Introduction to Econometrics; and Jeffrey Wooldridge, Introductory Econometrics. The material in the textbooks will be complemented with recent research papers and chapters from other books. A full reading list will be distributed at the beginning of the course.

Students have to complete a data analysis exercise by the end of the seventh week of LT which counts for 25% of the overall mark. A group project, to be developed and presented, counts for 10% of the overall mark. A final three-hour examination counts for the remaining 65% of the overall mark.