Spring 2010 Course Description

Advanced Topics in Public Policy

Section Title: Evaluation Of Social Policies And Programs
Instructor(s): Chandler Stolp
Course: P A 388K - Advanced Topics in Public Policy
(previously Seminar in Topics in Public Policy)
Unique Number: 62525
Day & Time: Fridays, 9:00 AM - 12:00 PM
Room: SRH 3.216
Waitlist Information:For LBJ Students: UT Waitlist Information

Description: This PhD-level course offers an introduction to the practical application of microeconomic principles and cutting-edge statistical techniques to the evaluation of social programs. The substantive focus will be on programs in health, education, welfare, and workforce training, focusing especially on cases drawn from Latin America. Students will be invited to work through a series of concrete program evaluations conducted for a number of international and other organizations ranging from the World Bank to NGOs to the governments of Mexico, Bolivia, and Indonesia. While the course does touch on cost-benefit analysis (prospective evaluation before a program is in place), the primary focus is on the design and execution of program evaluations (the assessment of on-going programs or of programs after the fact). This will call for a solid treatment of:

Readings draw from the literature on program evaluation, quasi-experimental design, and microeconometrics. The econometrics of evaluation has become a particularly exciting area of research in recent years. While oftentimes challenging, it has important implications on public policy analysis. Students will write occasional commentaries on real-world studies and analyze large real-world datasets using the methods and techniques developed in the course. Students willl be evaluated in terms of the quality of their participation in class discussion and on their performance on take-home exercises that will be assigned approximately every two weeks.

Prerequisites: Open to qualified PhD and masters students. Requires that students have a reasonable command of basic graduate-level econometrics (eg, familiarity with maximum likelihood estimation and logit/probit analysis) and be comfortable working with summation and matrix notation.

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