PMEP 552, Advanced Health Econometrics I
Units: 4
Fall 2017—Monday and Wednesday, 8-10am
Location: VPD LL101
Instructor: Rebecca Myerson and John Romley
Office: VPD Office 414E and VPD 212A
Office Hours: Upon request
Contact Info: and
Course Description
This course is designed to expand students’ knowledge of econometric methods. In particular, the course will develop econometric reasoning and skills through practical applications. The course builds on the foundation of PMEP 551 (Introduction to Health Econometrics), and prepares students for advanced study of microeconometrics, including PMEP 553 (Advanced Health Econometrics II). The course is appropriate for Ph.D. students in applied economics (including pharmacoeconomics), as well as master’s students in economics with an interest in econometric applications. Specific areas to be covered include: instrumental variables, policy evaluation, panel models, nonlinear regression, generalized method of moments, simulation methods, dichotomous and multinomial outcomes, count and related models, survival analysis, and structural econometric analysis. The course emphasizes, but is not limited to, applications to health economics.
Learning Objectives
Upon completion of this course, students should be able to:
· implement a wide range of microeconometric techniques
· critically assess applied microeconometric studies
· identify empirical strategies appropriate to particular research questions and data structures
· independently perform a variety of data preparation, programming and analytic tasks in Stata
Prerequisite(s): PMEP 551 or equivalent
Concurrent Enrollment: None
Recommended Preparation: None
Software Required: Stata
Syllabus for PMEP 552, Page 7 of 6
Syllabus for PMEP 552, Page 7 of 6
Required Readings
Textbooks
· Jeffrey Woolridge’s Introductory Econometrics, 5th edition. (referred to as Woolridge below)
· Joshua Angrist and Jorn-Steffen Pischke’s Mostly Harmless Econometrics: An Empiricist’s Companion. (referred to as AP below)
· Colin Cameron and Pravin Trivedi’s Microeconometrics: Methods and Applications. (referred to as CT1 below)
· Colin Cameron and Pravin K. Trivedi, (2010), Microeconometrics Using Stata (revised edition), Stata Press (referred to below as CT2 below)
Additional readings
Social experiments and the evaluation problem:
· LaLonde R. “Evaluating the Econometric Evaluations of Training Programs with Experimental Data,” American Economic Review 76(4) September 1986 604-620.
· Baicker, K., Taubman, S. L., Allen, H. L., Bernstein, M., Gruber, J. H., Newhouse, J. P., … Smith, J. (2013). The Oregon experiment--effects of Medicaid on clinical outcomes. The New England Journal of Medicine, 368(18), 1713–22. doi:10.1056/NEJMsa1212321
Instrumental variables:
· Imbens, G. (2010). Better LATE than nothing: Some comments on Deaton (2009) and Heckman and Urzua (2009). Journal of Economic Literature, 48(June), 399–423. Retrieved from http://www.jstor.org/stable/10.2307/20778730
Regression discontinuity
· Imbens, G., & Lemieux, T. (2008). Regression discontinuity designs: A guide to practice. Journal of Econometrics, 142(2), 615–635. doi:10.1016/j.jeconom.2007.05.001
Matching
· Austin, P. (2008). A critical appraisal of propensity score matching in the medical literature between 1996 and 2003. Statistics in Medicine, 27(2037-2049). doi:10.1002/sim
· Ho, D. E., Imai, K., King, G., & Stuart, E. a. (2007). Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference. Political Analysis, 15(3), 199–236. doi:10.1093/pan/mpl013
· King, G., Gakidou, E., Ravishankar, N., Moore, R. T., Lakin, J., Vargas, M., … Llamas, H. H. (2007). A “Politically Robust” Experimental Design for Public Policy Evaluation, with Application to the Mexican Universal Health Insurance Program. Journal of Policy Analysis and Management, 26(3), 479–506. doi:10.1002/pam
Description of Assignments
Problem sets will consist of questions on concepts and methods (“pencil and paper”) and questions involving the application of the methods to data using Stata.
In addition, students will prepare and present a pilot research project. Students will also complete practice problems in class, which are graded chiefly on completeness.
Grading Breakdown
Assignment / Percent of Final GradeProblem sets / 10%
In-class practice problems / 10%
In-class presentation of pilot research project / 10%
Class participation / 5%
Midterm exam / 30%
Final exam / 35%
Grading Scale
Course final grades will be determined using the following scale
A 95-100
A- 90-94
B+ 87-89
B 83-86
B- 80-82
C+ 77-79
C 73-76
C- 70-72
D+ 67-69
D 63-66
D- 60-62
F 59 and below
Course Schedule: A Weekly Breakdown
Weeks 1-2
/ Review of linear regression / · CT1 4.1-4.7 / Assignment 1 posted/ Models for panel data /
· Wooldridge Ch. 13-14
· CT1 21
/Weeks 2-3
/ Instrumental variables / · Wooldridge Ch. 15· CT1 4.8-4.10
/ Limited dependent variables / · Wooldridge Ch. 17
· CT1 14
Week 4
/ Practical empirical concerns:Measurement error
Missing data and possible solutions / · Wooldridge Ch. 9.4-9.5
· CT1 26.1-26.2
· CT1 27.1-27.3 / Assignment 1 due; Assignment 2 posted
Week 5
/ Regression and causality; Lalonde’s critique of non-experimental evaluations / · AP 51-59· CT1 25.1-25.3
· Lalonde 1986
/ Randomized social experiments and the evaluation problem / · AP 12-24
· CT1 3.3
· Baicker et al 2013 / Assignment 2 due; additional practice problems posted
Week 6
/ Matching methods / · CT1 25.4; Austin 2008· King et al, 2007; Ho et al 2007
/ Regression discontinuity design / · AP 251-268
· CT1 25.6
· Imbens and Lemieux 2008
Week 7
/ Difference in differences / · AP 227-243· CT1 25.5
/ Pre-midterm review
Week 8 class 1
/ Midterm / MidtermWeek 8 class 2-week 9
/ Generalized method of moments and maximum likelihood / · CT1 6· CI1 5.1-5.7 / Assignment 3 posted
Week 10
/ Mulltinomial outcomes; nonlinear regression / · CT1 15 except 15.9, 12· CT2 4, 15
· CT1 5.8 on; CT2 10
Week 11
/ Count and related models / · CT1 20· CT2 10 / Assignment 3 due; Assignment 4 posted
Week 12
/ Survival analysis / · CT1 17Week 13
/ Nonlinear panel models / · CT1 18, 23· CT2 18 / Assignment 4 due
Week 14
/ Structural econometric analysis / TBAWeek 15
/ In-class presentations of pilot researchFINAL
/ Date: For the date and time of the final for this class, consult the USC Schedule of Classes at www.usc.edu/soc.Statement on Academic Conduct and Support Systems
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Syllabus for PMEP 552, Page 7 of 6