| Call Number | 10555 |
|---|---|
| Day & Time Location |
W 11:00am-12:50pm To be announced |
| Points | 3 |
| Grading Mode | Standard |
| Approvals Required | None |
| Instructor | Alan S Yang |
| Type | SEMINAR |
| Method of Instruction | In-Person |
| Course Description | Prerequisites: SIPA U6501 The goal of this course is to provide students with a basic knowledge of how to perform some more advanced statistical methods useful in answering policy questions using observational or experimental data. It will also allow them to more critically review research published that claims to answer causal policy questions. The primary focus is on the challenge of answering causal questions that take the form Did A cause B? using data that do not conform to a perfectly controlled randomized study. Examples from real policy studies and quantitative program evaluations will be used throughout the course to illustrate key ideas and methods. First, we will explore how best to design a study to answer causal questions given the logistical and ethical constraints that exist. We will consider both experimental and quasi- experimental (observational studies) research designs, and then discuss several approaches to drawing causal inferences from observational studies including propensity score matching, interrupted time series designs, instrumental variables, difference in differences, fixed effects models, and regression discontinuity designs. As this course will focus on quantitative methods, a strong understanding of multivariate regression analysis is a prerequisite for the material covered. Students must have taken two semesters of statistics (SIPA U6500 & U6501 or the equivalent) and have a good working knowledge of STATA |
| Web Site | Vergil |
| Department | International and Public Affairs |
| Enrollment | 0 students (23 max) as of 10:06AM Friday, November 15, 2024 |
| Subject | School of International & Public Affairs |
| Number | U8500 |
| Section | 001 |
| Division | School of International and Public Affairs |
| Open To | SIPA |
| Section key | 20251SIPA8500U001 |