|Section Title:||Multivariate Analysis for Policy Research|
|Course:||P A 397C - Applied Quantitative Analysis II|
|Day & Time:||Mondays, Wednesdays, 9:00 AM - 10:30 AM|
|Waitlist Information:||For LBJ Students: UT Waitlist Information|
Description: This course examines the application of advanced statistical techniques to public policy analysis. The use of empirical techniques for developing an understanding of a policy issue, in analytical modeling, in making forecasts and in evaluating policies and programs will be covered. The limitations of empirical techniques in policy analysis will also be examined. The course will cover multivariate regression analysis, use of categorical variables as independent and dependent variables, classic problems in regression analysis, analysis of panel date, forecasting, time series modeling, and simultaneous equations models.
The course is cast in an applications mode rather than a theoretical or mathematical mode. Students will also become familiar with the SAS statistical package through several homework sets.
Student progress will be evaluated on three types of work: (1) four problem sets (20% of the final grade) are designed to demonstrate competency over fundamentals and to provide practice in the application of econometric methods to policy issues; (2) two exams (each accounting for 25% of the final grade); and (3) a term paper (30% of the final grade) due on the last day of class.
For the term paper, each student will develop research hypotheses, identify an appropriate data set for testing the hypotheses, perform a regression analysis, test for the common problems of regression analysis, and interpret the results. Each student will make a presentation of the term paper in class.
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