Fall 2017 - 61095 - PA 397 – Introduction to Empirical Methods for Policy Analysis

Introduction to Empirical Methods for Policy Analysis


Email:                  michaelmeyer@utexas.edu


In the modern era, the discourse of public policy and management has been marked by an ever-increasing focus on the effective use of data to drive analysis and decision making. This course is an introduction to the use of quantitative tools in those contexts. It is designed to build students’ skills in: applying modeling techniques to select an optimal course of action; interpreting and learning from data toward the purpose of making reasoned arguments and sound decisions; and understanding others’ arguments and evaluating their strength.

The course will cover a range of topics within the major themes of optimization and mathematical programming, decision making using probabilistic information, descriptive and inferential statistics, and regression analysis/model building, all with a focus on applying these analytical tools in a policy/management environment. The course format will combine lectures and discussion with outside reading and individual/group work. Students should expect a moderate but not heavy reading load; depending on each student’s prior quantitative training, practice exercises and assignments may require considerable effort. Students will be exposed to several Excel Add-ins that facilitate quantitative analysis and modeling, and assessment will occur through class participation, six problem sets and two exams.

Students must be comfortable with the basic elements of algebra, calculus, descriptive statistics, probability and symbolic notation (such as the use of Greek characters and subscripts, interpreting summations, etc.).  The course is typically taken in the fall semester of a student’s first year. In the second course of the quantitative methods sequence students acquire more specialized knowledge and skills in a focused area of their choosing. The introductory course provides the foundation for the quantitative methods sequence and provides necessary skills for other courses in the LBJ curriculum.

Primary learning objectives:

  1. Develop modeling tools to evaluate real-world problems and identify an optimal course of action.
  2. Acquire the skills needed to explore, analyze, and learn from data in an intelligent way, and apply what is learned to decision-making processes in a policy environment.
  3. Hone the necessary skills to effectively interpret and evaluate the strength of quantitative methods deployed in analyses, reports, (non-)scholarly articles and other venues of policy discourse.

Requirements and Expectations

Students will be evaluated based on the following items (percent of final grade and date due):

  1. Problem Set 1 (7%)
  2. Problem Set 2 (9%)
  3. Problem Set 3 (9%)
  4. Mid-TermExam (20%)
  5. Problem Set 4 (7%)
  6. Problem Set 5 (9%)
  7. Problem Set 6 (9%)
  8. Final Exam (20%)
  9. Class Participation (10%)

Letter grade ranges and corresponding numerical grade points will be in accordance with university rules.


There is no single text assigned for this class. Course materials will be drawn from several sources, and electronic copies will be made available through Canvas. PowerPoint slides, class handouts, problem sets/solutions and any other course materials will also be posted to Canvas. Materials may be supplemented or revised during the course of the semester. Supplemental or revised materials will be announced in class to the extent possible. However, students are highly encouraged to check Canvas prior to each class meeting and will be held accountable for any and all materials posted there.


SRH 3.124