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Fall 2011 - 61470 - PA397 - Introduction to Empirical Methods for Policy Analysis

Instructor(s): Zarnikau, Jay
Unique Number: 61470
Day & Time: T 6:00 - 9:00 pm
Room: SRH 3.219/216
Waitlist Information:For LBJ Students: UT Waitlist Information
Course Overview

This course helps students develop an understanding of how basic quantitative tools are used in policy analysis. The major concepts discussed include modeling, optimization, sensitivity analysis, statistical inference, estimation, and prediction. These concepts are covered in the context of applications such as constrained decisionmaking based on calculus and on linear programming; policy choices with probabilistic information; evaluating and updating information with Bayesian techniques; estimating the impact of policy factors using regression models; and practical methods for forecasting. As the first course in the quantitative sequence, the emphasis is on broad exposure of techniques and appreciation of their contributions as well as their limitations in policymaking. Students must have fulfilled prerequisites in college-level algebra, calculus, and statistics before enrolling in this course. It is usually taken during the fall semester of the first year.
 

Section Description

This course introduces approaches to problem solving and quantitative analysis used in public policy analysis and the social sciences. It emphasizes the art and skill of converting problem descriptions into quantitative models, and the analysis and interpretation of such models.

Basic concepts in probability theory and applied statistics will be covered. Following a discussion of data sources and sampling methods, sample data will be used to make inferences about the parameters of larger populations. Relationships among variables will be analyzed.

We will also look at how quantitative methods can be applied to support decision-making through decision trees. The sensitivity of a decision to changes in assumptions will be studied.

Mathematical optimization (primarily, linear programming) will be introduced as a technique for identifying the optimal solution to a problem.

The course focuses on concepts and applications course, as opposed to formal proofs and derivations. Students will make extensive use of Microsoft Excel computer spreadsheets for homework assignments.