|Section Title:||Program Evaluation|
|Course:||P A 397C - Advanced Empirical Methods for Policy Analysis
(previously Applied Quantitative Analysis II)
|Day & Time:||Mondays, Thursdays, 10:30 AM - 12:00 PM|
|Waitlist Information:||For LBJ Students: UT Waitlist Information|
Description: Each year, the Federal government spends billions of dollars on the Head Start program for young children. How well does it prepare kids for school? Could it do better? In FY 2006, Texas will spend $240 million to divert convicted adult felons from prison to community programs. Do these programs protect the public and rehabilitate the offenders? This year the City of Austin will spend $2.9 million to prevent chronic diseases such as diabetes and atherosclerosis. Is this money well spent? Should we spend more?
To an increasing extent, public policymakers and managers rely on program evaluation to answer questions like these. In this course, we will consider some of the techniques of program evaluation: "meta-analysis" to sort through previous studies to identify what has worked elsewhere and in the past; intensive interviewing, fiscal auditing, and participant observation to see what a program (really) does; development of performance measures, examination of archival records, surveys of participants, and other follow-up techniques to see how well the program succeeds; and statistical methods of linking program activities to long-run outcomes. Special emphasis will be placed on interrupted time-series methods ? the before-and-after comparisons that are often the most cost-effective method available for measuring program impact. Case studies will be drawn from programs in education, health care, employment and training, criminal justice, and other fields.
Lots of public programs are worthy of evaluation, and the best way to learn is by doing. So each student will participate in planning and conducting an evaluation of a local program. Although only some of the methods considered are statistical techniques, students will feel most comfortable if they recall and understand statistics through multiple regression
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