Quantitative Methods for Policy Evaluation

HPM 543 Subject & Catalog Number

Description

This course introduces students to the analytic tools they need to evaluate policy interventions, social programs, and health initiatives.
By the end of the course, students will be able to identify research questions amenable to experimental or quasi-experimental techniques and design thoughtful studies to help answer them. This will include assessing the adequacy of available data, implementing econometric analyses, interpreting results from quantitative studies, and identifying the policy implications of quantitative results. The course focuses on health-related interventions such as health insurance programs and public health campaigns, but the techniques are broadly applicable to other areas of study, such as welfare and education.
The course also provides a practical introduction to various quantitative methods for policy evaluation, including randomization, instrumental variables, regression discontinuity, time series, difference-in-differences, and matching.
Course Note: The course material is quantitative and builds on a base of statistics fundamentals, including knowledge of hypothesis testing and confidence intervals, as well as basic facility with algebraic and regression techniques. The prerequisite is a course in basic statistics and probability, such as ID 201, BST 201, or an equivalent course. During the course, students will analyze data sets using R statistical software. Familiarity with at least one statistical software package, such as Stata or R, is helpful but not required.

Prerequisites: A course in basic statistics and probability, such as ID 201, BST 201, BST 202 & 203, BST 206 & 207, BST 206 & 208, BST 210, BST 213, EPI 208, or an equivalent course. Concurrent enrollment is allowed.