Advanced Quantitative Methods

Course Code: PUBLG088

Course Tutor: Dr Slava Mikhaylov (Department of Political Science)

Assessment: One 3,000 word essay

Credit Value: 15 credits

About this course

The course introduces students to concepts and techniques essential to the analysis of public policy issues. Students are introduced to regression-based methods that are used in the design and quantitative evaluation of causal effectiveness of public policies. The objective of the course is for students to learn how to conduct (and how to critique) empirical studies in quantitative policy analysis and in social sciences more generally. Accordingly, the emphasis of the course is on empirical applications. The mathematical component will be kept to a minimum and introduced only as needed. First part of the course reviews the basics of linear and nonlinear regression modeling. Second part introduces the methods used to assess policy interventions and causality. These include randomized experiments, natural or quasi-experiments, time series and panel data, differences-in-differences estimation, instrumental variables, matching and regression discontinuity designs. The course also provides students an opportunity to become proficient in the use of computer software widely used in analyzing quantitative data.

On completing the course students will be able to demonstrate a comprehensive understanding of, familiarity with, and critical evaluation of recent advances in quantitative policy analysis. Students will be able to apply quantitative techniques to evaluate public policy interventions using standard statistical packages. Knowing how to evaluate public policy is an integral component in developing policy alternatives. Apart from personal development, this will also give students of this course an advantage in gaining employment in public and private sectors that seek candidates able to contribute to the development, application, and evaluation of public policy.