Quantitative Analysis II for Internation

Pre-req: Quant I. This course introduces students to regression analysis as a tool for policy analysis and program evaluation (i.e., econometrics). As future practitioners and policymakers, your professional decisions will impact the world in many ways. This course will equip you with the empirical skills needed to evaluate these impacts and assess the causal effects of programs and policies.

The first half of the course will focus on the fundamentals of multiple regression analysis (including a review of Quant I), emphasizing causal inference. The second half builds on this foundation, introducing experimental and non-experimental methods widely used in empirical research and program evaluation.

Note that this is not a math course. Instead of solving math problems, you will be asked to articulate the statistical concepts we have learned and how they relate to different policy settings. Beyond the technical and conceptual foundations, a key emphasis is developing the ability to apply and explain statistical concepts in non-technical language. This skill is crucial for communicating effectively with policymakers who are not statistical experts, as you would be expected to do in many jobs and with most audiences. This course will also prepare you to take any of SIPA’s Quant III courses. This course aims to achieve three broad goals: 

1. Develop the technical foundations and intuition to become intelligent consumers of statistical analysis for policy research and program evaluation. This enables you to assess empirical studies and articulate findings in non-technical language critically.
2. Understand causal thinking and its role in interpreting data analysis and empirical studies.
3. Build the skills to apply and explain statistical concepts in accessible language, fostering effective communication with policymakers and non-experts.