PP455E      Half Unit
Empirical Methods for Public Policy

This information is for the 2019/20 session.

Teacher responsible

Prof Daniel Sturm

Availability

This course is compulsory on the Executive Master of Public Administration and Executive Master of Public Policy. This course is not available as an outside option.

Pre-requisites

There are no formal pre-requisites, but recommended advance readings will be distributed ahead of the course. Familiarity with the material covered in the EMPA/ EMPP Introduction to Statistics module is assumed.

Course content

The course introduces students to the quantitative evaluation of public policies. The focus of the course is on practical applications of techniques to test the effectiveness of public policy interventions. The course begins with an overview over the key benefits of randomized experiments in the evaluation of public policies. Next the course covers a number of techniques that are widely used in the evaluation of public policies, including difference-in-differences regressions, regression discontinuity approaches and matching. It concludes with an introduction to cost-benefit analysis.

Teaching

A one-week modular teaching block.

Formative coursework

One mock examination will be provided.

Indicative reading

A full reading list will be distributed at the beginning of the course.

Assessment

Project (50%, 2000 words) and online assessment (50%).

Please note that online assessments take place on the third Friday after module teaching concludes. The project will consist of a 2,000 word data analysis exercise due on the sixth Friday after module teaching concludes. Further details will be provided at the Executive MPA/ Executive MPP programme inductions.

Key facts

Department: School of Public Policy

Total students 2018/19: 2

Average class size 2018/19: Unavailable

Controlled access 2018/19: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Problem solving
  • Application of numeracy skills
  • Specialist skills