Dr Alexandra Cirone

This course is compulsory on the Master of Public Policy. This course is not available as an outside option to students on other programmes. This course uses controlled access as part of the course selection process. For information on controlled access courses, including eligibility, application processes, deadlines, and departmental contact details, please refer to the Controlled Access Courses webpage.

Compulsory course for MPP students. Not available as an outside option.

MPP students should select the course by 12 noon on the Friday before the start of Autumn Term.

The course is designed to equip students with the tools of quantitative data analysis for the social sciences. Students will be introduced to several econometric approaches that researchers and policymakers use for the evaluation of public policy, and will be taught how to perform data analysis and data visualization using statistical software. The course emphasis is on the practical application of these skills and tools to real-life situations and policy-making interventions, such that students will understand when each tool can be applied and when not. Topics covered include data measurement and visualization, causal inference, regression analysis, randomised control experiments, design-based inference, and cost-benefit analysis.

16.5 hours of seminars, 11 hours of help session and 22 hours of lectures in the Autumn Term.

Students will submit a proposed topic for their final project, and receive feedback on potential datasets that could be used.

Thinking Clearly with Data: A Guide to Quantitative Reasoning and Analysis, by Ethan Bueno de Mesquita and Anthony Fowler

Data Analysis for Social Science: A Friendly and Practical Introduction, by Elena Llaudet and Kosuke Imai

Quantitative Social Science: An Introduction, by Kosuke Imai

The Effect, by Nick Huntington-Klein

 The given texts are preparatory reading only. A full reading list will be provided at the start of the course.

Exam (60%), duration: 180 Minutes, reading time: 15 minutes in the January exam period.

Problem sets (10%).

Project (30%).

Exam (60%): The exam’s duration is 180 Minutes (with 15 minutes reading time) and will take place during the January exam period. It will be in-person and invigilated.

Final Project (30%): Each student will complete a final project to demonstrate what they have learned, involving both a written and presentation component.

Class Exercises (10%): Students will submit coding and application exercises in advance of seminars.