Fall 2018 - 61050 - PA 397 – Introduction to Empirical Methods for Policy Analysis
Introduction to Empirical Methods for Policy Analysis
Scope and Objectives
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
Proficiency in differential calculus and statistical reasoning is prerequisite to this section of IEM. Ability to do calculation or use software is irrelevant —what’s important is the use of calculus and statistics as thinking tools. An optional evening tutorial will be offered weekly. Abstention from long-hand note-taking in class is requested.