Lectures:  TR 1:30  2:45 p.m.  102 SWKT 
Labs:  T 3:00  4:50 p.m.  102 SWKT 
R 3:00  3:50 p.m.  102 SWKT 
The home page for Public Policy 604 is http://goodliffe.byu.edu/604/. Check the home page often for announcements, corrections, instructions for assignments, syllabus, etc. You should also check your email regularly. I suggest that you exchange phone numbers and/or email addresses with other students in the class.
I will hold office hours on Tuesdays and Thursdays 34 p.m. I am also available at most other times if you make arrangements with me. (Other good times: Tuesdays at noon; Thursdays at 11 a.m.) I encourage you to come by to talk about assignments in the class, suggestions for improving the class, politics and current events, the perils of student life, or for any other reason. (Suggested topics: playing the organ, practicing yoga, student evaluations, Choose to Give program, BYU tuition.)
This course explores advanced topics in econometrics, building on basic linear regression learned in Public Policy 603. This course is designed to help you
As a result of its recent accreditation experience (and increasing emphasis from the Department of Education to measure educational outcomes, e.g. NCLB), each program at BYU has developed a set of expected student learning outcomes. These will help you understand the objectives of the curriculum in the program, including this class. To learn the expected student outcomes for the Public Policy Program go here.
The specific learning objectives that this course fulfills include:
This is the second semester in a twocourse sequence. The first semester was Public Policy 603, and is thus a prerequisite for this course. That course covered basic statistics, ordinary least squares and its pathologies, and logit/probit models. Econ 388 or PlSc 328 may partially substitute for PPol 603. If you have not taken PPol 603, you need to speak to me before proceeding.
We will emphasize application and interpretation over theory. Thus, in addition to the textbook, we will read articles that apply these methods to problems in public policy.
The course will be run primarily as a lecture. However, I actively encourage questions, interruptions, cries for help, protests of disbelief, etc. You will never be penalized for participatingeven when this takes the form of vague complaints like, "I've got no clue why we are doing this stuff!" I urgeindeed, I expectyou to take advantage of the chance to talk with me during office hours.
A Chinese proverb (supposedly) says, "I hear and I forget, I see and I remember, I do and I understand." This philosophy drives the requirements of the class.
Weekly Assignments  30% 
Midterm Exam  15% 
Final Exam  30% 
Research Project  25% 
All assignments are due at the beginning of class. You will most likely turn these in electronically to the TA. I will not accept late assignments. The primary reason for no late assignments is so that we can discuss the assignment in class immediately after it is turned in. If you anticipate a problem with submitting an assignment when it is due, speak to me before the assignment is due so that we can try to work out an alternative arrangement.
To understand statistics, you must use statistics. To facilitate understanding, there will be weekly assignments that may include any or all of the following:
You may work together on these assignments (in groups of two or at most three), but you must write up your answers separately. I give much more detailed instructions on how to report your work together in the Academic Honesty section below. Generally, if you use other persons' work, or make changes to your own work without inquiring or understanding what you did incorrectly, then you are trying to get a grade using someone else's knowledge. Giving or receiving answers in this manner is not permitted in this course. If you do not learn how to analyze or solve problems on your own, you will have difficulty on the exams and research project. Generally, weekly assignments will be distributed and due on Thursdays.
There is a midterm and final exam. These are both takehome exams. They will require you to solve problems similar to case studies in the weekly assignments. You are not allowed to consult with anyone on these takehome exams. The final exam will cover material for the whole semester. The exams will be discarded at the end of the Summer 2011 term.
Students will write and present a paper on a topic of their choosing. The project will allow you the opportunity to apply the skills that we will develop in this class to actual data and problems. You may pursue any topic of your choice, subject to instructor approval. (Of course, one requirement is that you have the necessary data.) There are a number of deadlines that must be met, noted on the course schedule.
I strongly recommend that you consult with me and the teaching assistant through all phases of your research. I may be able to help you select a feasible topic, find data, or comment on your statistical model.
Proposal 
2% 
Outline and Bibliography 
3% 
Poster 
25% 
Final Paper 
70% 
Turn in a (no longer than) onepage proposal outlining the research question you wish to address, and how you plan to address it. Discuss why the research question is interesting, and possible data sources.
Turn in a (no longer than) twopage outline of your paper sketching out the argument you plan to make and/or hypotheses you will test, and how you will do it. Include an annotated bibliography of sources whose work you build on. Also list where you have obtained your data.
Submit and present a poster to the Mary Lou Fulton Conference. Details found here.
The paper's technical level may be higher than the presentation's. However, you should still explain what your statistical results mean in layman's terms. In grading the paper, I will consider how well you have used material from the course, how well you have used statistical analysis to test your hypotheses, if the analysis is actually correct (numerical accuracy and correct interpretation), how well you use charts and graphs, logic and organization of the paper, and the usual grammatical and spelling concerns. Follow the examples of published papers we read in class and the outline given in Chapter 19 of Wooldridge. The papers may be picked up in the Political Science office (745 SWKT) after they are graded. The papers will be discarded at the end of the Summer 2011 term.
As a statistical analyst, it is very important that you are aware of the limitations of your research. Under what circumstances do your results hold? Likewise, which circumstances would make them invalid? If you are unable to conduct the ideal analysis (perhaps due to resource constraints), explain what the proper approach would be. If you were able to use this superior approach, how would the results likely differ from the results you have?
The course is graded on a modified curve, using statistical principles that will be explained in the course.
Putting these statements together, the university expects an average graduate student to work more than 9 hours a week in a 3 credithour course to achieve excellence. The work load in this course is heavy but manageable.
Students who have succeeded in this course have the following characteristics. They
Tuesdays and Thursdays after class will be spent in the FHSS Computer Lab on the 1st floor. We will learn how to implement the econometric tools in Stata and other statistical programs, such as SPSS, SAS, and Excel. This is to increase flexibility and marketability for future work opportunities. Each week, the labs will cover the commands necessary to do the weekly assignments, go over past assignments, and review the material generally. I expect all students to have a working knowledge of the Windows operating system (i.e., what backslashes mean, how to use a mouse, how to use pulldown menus, etc.).
Please arrive in the Computer Lab (102 SWKT) before class starts to start up the computer and have everything ready to go when class starts.
You may find it useful to purchase your own copy of Stata. If you do not purchase your own copy, you need to plan ahead to use the computers in SWKT. Since some data sets we use have more than 1000 observations, you will need to purchase Stata/IC or Stata/SE.
From the Academic Honesty section of the BYU Honor Code: "The first injunction of the BYU Honor Code is the call to `be honest.' Students come to the university not only to improve their minds, gain knowledge, and develop skills that will assist them in their life's work, but also to build character. `President David O. McKay taught that character is the highest aim of education' (The Aims of a BYU Education, p. 6). It is the purpose of the BYU Academic Honesty Policy to assist in fulfilling that aim" (cite).
"BYU students should seek to be totally honest in their dealings with others. They should complete their own work and be evaluated based upon that work. They should avoid academic dishonesty and misconduct in all its forms, including but not limited to plagiarism, fabrication or falsification, cheating, and other academic misconduct" (cite). Read the full version here (parts attached to the original paper syllabus).
A colleague (Mitch Sanders, former professor at Notre Dame) has already explicated these issues specifically for political science. Please read here (also attached to the original paper syllabus).
If you write a paper for another course (past or present) that uses the same topic as a paper for this course, you need to approve it with me first, and then you must turn in to me a copy of the paper from your other course.
In this class, you need to acknowledge the contributions of others toward your assignments. I have taken the following guidelines from MIT's Unified Engineering class. I have changed and added various words where appropriate:
"The fundamental principle of academic integrity is that you must fairly represent the source of the intellectual content of the work you submit for credit. In the context of [PPol 604], this means that if you consult other sources (such as fellow students, TA's, faculty, literature) in the process of completing homework [(or Stata codes)], you must acknowledge the sources in any way that reflects true ownership of the ideas and methods you used."
"Discussion among students to understand the homework problems or to prepare for [exams] is encouraged."
"COLLABORATION ON HOMEWORK IS ALLOWED UNLESS OTHERWISE DIRECTED AS LONG AS ALL REFERENCES (BOTH LITERATURE AND PEOPLE) USED ARE NAMED CLEARLY AT THE END OF THE ASSIGNMENT. Wordbyword copies of someone else's solution or parts of a solution handed in for credit will be considered cheating unless there is a reference to the source for any part of the work which was copied verbatim. FAILURE TO CITE OTHER STUDENT'S CONTRIBUTION TO YOUR HOMEWORK SOLUTION WILL BE CONSIDERED CHEATING."
"Study groups are considered an educationally beneficial activity. However, at the end of each problem on which you collaborated with other students you must cite the students and the interaction. The purpose of this is to acknowledge their contribution to your work. Some examples follow:
Unfortunately, some BYU students, who have committed to the Honor Code, profess ignorance of or attempt to find loopholes in the previous guidelines. As a result of sad experience, I repeat the following guidelines and add clarifications:
Title IX of the Education Amendments of 1972 prohibits sex discrimination against any participant in an educational program or activity that receives federal funds. The act is intended to eliminate sex discrimination in education. Title IX covers discrimination in programs, admissions, activities, and student to student sexual harassment. BYU's policy against sexual harassment extends not only to employees of the university but to students as well. If you encounter unlawful sexual harassment or gender based discrimination, please talk to your professor; contact the Equal Employment Office at 4225895 or 3675689 (24 hours); or contact the Honor Code Office at 4222847.
Brigham Young University is committed to providing a working and learning atmosphere which reasonably accommodates qualified persons with disabilities. If you have any disability which may impair your ability to complete this course successfully, please contact the University Accessibility Center (2170 WSC, 4222767). Reasonable academic accommodations are reviewed for all students who have qualified documented disabilities. Services are coordinated with the student and instructor by the SSD office. If you need assistance or if you feel you have been unlawfully discriminated against on the basis of disability, you may seek resolution through established grievance policy and procedures. You should contact the Equal Employment Office at 4225895, D282 ASB.
All readings should be read before class for full understanding of the subject material.
There is one required book that is available for purchase at the BYU bookstore (see BooksPrice.com for a listing of bookstores and comparison of prices):
There are some ancillary materials (e.g. datasets) available here.
There are two additional statistical books from PPol 603 that we will also use:
There are other chapters and articles we will read that are available through links below. The chapters are on material not covered by the books:
Note: W=Wooldridge; RS=RabeHesketh and Skrondal; B=Baum; CGGM=Cleves, Gould, Gutierrez, and Marchenko
Date 
Topic 
Readings 
Assignments 

January 4 
Instrumental Variables  W:15; B:8 Gayer 

6 
2SLS  W:15 Ayres and Levitt 
Assignment 0 due 
11 
Simultaneous Equations  W:16 Berry, Fording, and Hanson 

13 
Applications  Angrist and Krueger Angrist and Evans 
Assignment 1 due 
18 
Difference in Differences  W:13 Decker, Mayer, and Glazerman 

20 
Variancecomponents Models  RS:2  Assignment 2 due 
25 
Randomintercept Models  RS:3  Proposal due 
27 
Randomintercept Models  RS:3  Assignment 3 due 
February 1 
Randomcoefficient Models  RS:4 

3 
Randomcoefficient Models  RS:4 Goodliffe and Hawkins 
Assignment 4 due 
8 
Panel Models: Econometric Approach  W:14; B:9 Grabowski and Morrisey 
Outline due 
10 
Panel Models: Multilevel Approach  RS:5  Assignment 5 due 
15 
Panel Models: Multilevel Approach  RS:5 

17 
Panel Models: Multilevel Approach  RS:5 Bloom, Hill, and Riccio 
Assignment 6 due 
22 
No classMonday teaching day 


24 
Hierarchical Binary Response Models  RS:6.18 Rigby, Ryan, and BrooksGunn 
Midterm due 
March 1 
Discretetime Survival Models  RS:8 

3 
Discretetime Survival Models  RS:8 Iceland 
Assignment 7 due 
8 
Continuoustime Survival Models  CGGM:2,8 

10 
Cox Model  CGGM:9.19.4 Marton 
Assignment 8 due 
15 
Cox Model  CGGM:10.510.6,11 Huang, Kunz, and Garfinkel 

17 
Parametric Models  CGGM:1214  Assignment 9 due 
22 
Examples and Posters  Quercia and Spader  
24 
Stationarity  W:11 LewisBeck and Alford 
Poster due (28) 
29 
Cointegration  W:18 Chinn 

31 
Regression Discontinuity  Shadish, Cook, and Campbell:7 

April 5 
Regression Discontinuity  Imbens and Lemieux Butler and Butler 
Assignment 10 due 
7 
No classPoster Session 


12 
Review  Final Paper due Final Exam distributed 

19 
Final Exam due 
Public Policy 604 home page
Jay Goodliffe's home page
This page is http://goodliffe.byu.edu/604/syllabus.htm