Fall 2017 - 61090 - PA 397 – Introduction to Empirical Methods for Policy Analysis
Introduction to Empirical Methods for Policy Analysis
This course is an introduction to a wide range of basic quantitative tools pertinent to policy analysis and management.
The primary emphasis of this section is to foster analytic thinking and communication skills through rigorous conceptual reasoning in the context of public policy. The mathematical and statistical techniques acquired through this thinking/communication learning process constitute a secondary objective—they are the anchoring stories and beneficial side-products.
Upon successful completion of this course, students will be prepared to take any section of Advanced Empirical Methods for Policy Analysis, which will focus on techniques within a specialized quantitative topic.
Structure of Content
This course is organized into six modules:
- Developing perspectives on the role of quantitative analysis in democratic politics
- Thinking about policy choices through the logic of calculus
- Visualizing policy issues and political constraints through linear programming
- Making decisions in environments of uncertainty and risk
- Guessing truth with bivariate statistical design
- Modeling reality with multivariate regression models
The learning process in this course is not driven by data crunching or use of software. Instead, all assignments in this course are based on conceptual reasoning and its application to practical problems. These assignments include:
- Problem sets involving group problem-solving about once every four weeks
- Individual-based exercises given out approximately once every five Fridays
- Final exam
Fulfillment of the quantitative prerequisites at the LBJ School—one semester each of differential calculus and basic statistics—is the minimum requirement. An optional Thursday evening tutorial will be offered weekly. Abstention from long-hand note-taking in class is requested.