Course Description
Empirical analysis of consumer problems and policies. Quantitative assessment of the severity of public problems. Econometric analysis of the effectiveness and efficiency of public and private policy responses to consumer problems.
Additional Requirements for Graduate Students:
Graduate students will complete a policy-related research
proposal. Also, they must read and report on (written report or
a mini-class lecture to undergraduates) an advanced policy book
(a classic or a new book recognized by policy professionals as
significant to field).
Athena Title
Cons An Evidence Based Policy
Undergraduate Prerequisite
FHCE 4000/6000 or FHCE 4000S/6000S or permission of department
Graduate Prerequisite
Permission of department
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Course Objectives
At the completion of this course, students will be able to: 1. Document consumer problems with relevant descriptive statistics and publicly available data. 2. Apply algorithms of constrained optimization and mathematical programming to problems of public and private policy decision- making. 3. Utilize quantitative research techniques and data from proprietary and public sources to conduct empirical analyses of public and private policies in terms of economic efficiency, impact on consumer welfare, and effectiveness (i.e., the ability of policy to reach its stated objectives). 4. Demonstrate proficiency of managing large data sets of consumer information with software platforms used in contemporary research on consumer economic well-being.
Topical Outline
1. Constrained and unconstrained decision optimization, linear and non-linear programming, data envelopment analysis. 2. Correlation and causation, natural and quasi-experiments. 3. Statistical and econometric tools of policy analysis: a. statistical hypotheses testing and inference, b. linear and non-linear regressions with cross-sectional and panel data, c. difference-in-difference techniques and regression implementations, d. applications of econometrics to measurement of associations and forecasting. 4. Datasets of information on consumer characteristics and behavior, e.g., Current Population Survey, Consumer Expenditure Survey, Health and Retirement Study, Survey of Consumer Finances, American Housing Survey, and others. 5. Analytics software and programming, e.g., Excel, SAS, R, Python.
Syllabus