Course Syllabus

Winter 2005

MW 8:00-8:50 a.m. in 280 SWKT

F 8:00-8:50 a.m. in 112 SWKT

Instructor: Jay Goodliffe

Office: 752 SWKT

Office Hours: MW 11 a.m. - 12 noon, or by appointment

Phone: 422-9136

e-mail: goodliffe@byu.edu

Teaching Assistant: Jon Wunderlich

Office: 1142 SWKT

Office Hours: 6 - 8 p.m. in 105 SWKT, or by appointment

Phone: 787-7155

e-mail: jonathan.wunderlich@gmail.com

Contents:

Home Page

Office Hours

Objectives

Prerequisites

Approach

Requirements

How to Succeed in this Course

Academic Honesty and Plagiarism

Discrimination

Readings

Computer Classes

Class Time

Schedule

Home Page

The home page for Public Policy 504 is http://fhss.byu.edu/polsci/Goodliffe/504/. 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 e-mail addresses with other students in the class.

Office Hours

I will hold office hours on Monday and Wednesday 11 a.m. to 12 noon. I am also available at most other times if you make arrangements with me. Feel free to talk to me after classes, or to contact me by email or voice mail. 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.

Objectives

This course explores advanced topics in econometrics, building on basic linear regression. This course is designed to help you

• Become an excellent consumer of quantitative arguments (particularly statistical arguments).
• Become an excellent regression and statistical analyst, able to utilize statistical techniques and quantitative data to support your own arguments.
• Explain quantitative and analytical results to a regular person.

Prerequisites

This is the second semester in a two-course sequence. The first semester was PPol 503 or Stat 511, and is thus a prerequisite for this course. That course covered basic statistics and ordinary least squares. Econ 388 or PlSc 328 may substitute for these, although there will be some overlap between those courses and this course. If you have not taken one of these courses, you need to speak to me before proceeding.

Approach

Given the small class size, this will not be a rigidly structured course. I welcome your input in determining what subjects we discuss, and how and when we cover them. There are some topics that we must cover, but others are flexible. We will be emphasizing 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 participating--even when this takes the form of vague complaints like, "I've got no clue why we are doing this stuff!" I urge--indeed, I expect--you to take advantage of the chance to talk with me during office hours.

Requirements

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.

All assignments are due at the beginning of class on the day designated in the course schedule. If you cannot make it to class, please leave the assignment with the department secretaries (in the Political Science office--745 SWKT) before class begins. Alternatively, you may email me the assignment. 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.

Weekly Assignments

To understand statistics, you must use statistics. To facilitate understanding, there will be weekly assignments that may include any or all of the following:

• statistical problems
• analyzing data and interpreting statistical results
• summary and critique of articles that use statistics

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 on Fridays at the end of class.

Exams

There are midterm and final exams. These are both take-home exams that you will have one week to finish. They will require you to solve problems similar to those in the weekly assignments. You are not allowed to consult with anyone on these take-home exams (except the instructor). The date for the midterm exam is tentatively given below. The final exam will cover material for the whole semester. The final exams may be picked up in the Political Science office (745 SWKT) after they are graded. The exams will be discarded at the end of the Summer 2005 term.

Research Project

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

Turn in a (no longer than) one-page 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.

Outline and Bibliography

Turn in a (no longer than) two-page 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.

Preliminary Analysis of Data

Turn in a (no longer than) four-page paper that gives a more detailed outline of your paper. This should also include a detailed description of your argument and statistical model (including what variables you use) and some relevant descriptive statistics for your data. You must have your data by this point.

Peer Review Draft

Each student will distribute his or her paper to an assigned student for peer evaluation. (In one of the weekly assignments, each student will evaluate a peer's paper, and return it with an evaluation sheet. Each peers will also give a grade to the instructor only. Finally, each author will grade his or her peer on how well he or she was able to constructively criticize author's arguments, and give specific suggestions on how to strengthen those arguments.) After incorporating the appropriate suggestions and criticisms, students will turn in their final paper (see below).

Presentation

All students will present their research during the last week or two of class. The presentation's technical level should be geared toward a generic public servant--you will have to explain what your statistical results mean. There will be a strict time limit, and you should be prepared to answer questions from the class and instructor. Further suggestions on presentations generally can be found here.

Final Paper

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. More detailed instructions can be found here. 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 2005 term.

How to Succeed in this Course

From the BYU 2004-2005 Undergraduate Catalog:

"The expectation for undergraduate courses is three hours of work per week per credit hour for the average student who is appropriately prepared; much more time may be required to achieve excellence" (p. 48).

From the BYU 2004-2005 Graduate Catalog:

"Graduate study is more rigorous than undergraduate study" (p. 23).

Putting these statements together, the university expects an average graduate student to work more than 9 hours a week in a 3 credit-hour course. This is my expectation as well.

This workload has been affirmed by President Bateman in his devotional addresses. On 7 September 1999, he stated, "It takes approximately three hours of study outside class for every hour in the classroom. If you take 15 hours of credit, you should allocate upward of 45 hours for study per week." On 19 September 2000, he advised, "Study daily--at least three hours for every hour in class."

Students who have succeeded in this course have the following characteristics. They

• Read the material before coming to class.
• Come to class with questions.
• Study in groups to make sure they understand the material.
• Spread work on the weekly assignments across the week.
• Work early and often on their research projects.
• Seek feedback from others.

Academic Honesty and Plagiarism

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.

"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." Read the full version here (parts attached to the original paper syllabus).

A colleague (Mitch Sanders, formerly of Notre Dame) has already explicated these issues specifically for social sciences. 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 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 504], 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. Word-by-word 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 Group Guidelines

"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:

1. You discuss concepts, approaches and methods that could be applied to a homework problem before either of you start your written solution. This process is encouraged. You are not required to make a written acknowledgment of this type of interaction.
2. After working on a problem independently, you compare answers with another student, which confirms your solution. You should acknowledge that the other student’s solution was used to check your own. No credit will be lost if the solutions are correct and the acknowledgments is made.
3. After working on a problem independently, you compare answers with another student, which alerts you to an error in your own work. You should state at the end of the problem that you corrected your error on the basis of checking answers with the other student. No credit will be lost if the solution is correct and the acknowledgment is made, and no direct copying of the correct solution is involved.
4. You and another student work through a problem together, exchanging ideas as the solution progresses. Each of you should state at the end of the problem that you worked jointly. No credit will be lost if the solutions are correct and the acknowledgment is made.
5. You copy all or part of a solution from a reference such as a textbook. You should cite the reference. Partial credit will be given, since there is some educational value in reading and understanding the solution. However, this practice is strongly discouraged, and should be used only when you are unable to solve the problem without assistance.
6. You copy verbatim all or part of a solution from another student. This process is prohibited. You will receive no credit for verbatim copying from another student when you have not made any intellectual contribution to the work you are both submitting for credit.
7. VERBATIM COPYING OF ANY MATERIAL WHICH YOU SUBMIT FOR CREDIT WITHOUT REFERENCE TO THE SOURCE IS CONSIDERED TO BE ACADEMICALLY DISHONEST."

Discrimination

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 422-5895 or 367-5689 (24-hours); or contact the Honor Code Office at 422-2847.

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 (422-2767). Reasonable academic accommodations are reviewed for all students who have qualified documented disabilities. Services are coordinated with the student and instructor by the UAC 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 422-5895, D-282 ASB.

Readings

All readings should be read before class for full understanding of the subject material.

There are two required books that are available for purchase at the bookstore (or any number of on-line bookstores, see AllBookStores.com or Campusbooks4less.com for a listing of bookstores and comparison of prices):

• Jeffrey M. Wooldridge. 2003. Introductory Econometrics: A Modern Approach, 2nd edition. Thomson.
• Tim Futing Liao. 1994. Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models. Sage.

I have placed Liao on reserve at the Lee Library.

There is another statistical book that is available for purchase:

• Peter Kennedy. 2003. A Guide to Econometrics, 5th edition. MIT Press.

The Kennedy book has a different approach than most statistics texts: in each chapter it discusses a set of concepts qualitatively, then the same concepts quantitatively, and finally discusses the minutiae of those concepts. (The 2nd edition, published in 1985, is on reserve at the library.) I would be happy to recommend other texts if you find these inadequate.

There are two additional statistical books on reserve at the library to help with the Stata computer program.

• Lawrence C. Hamilton. 2004. Statistics with Stata : updated for version 8. Brooks/Cole-Thomson Learning.
• Sophia Rabe-Hesketh and Brian Everitt. 2004. Handbook of Statistical Analysis Using Stata, 3rd edition. CRC Press/Chapman & Hall.

There are other articles we will read that are available through links below. These articles are examples of policy analyses using the tools we are learning:

• Gary T. Henry and Ross Rubenstein. 2002. "Paying for Grades: Impact of Merit-Based Financial Aid on Educational Quality." Journal of Policy Analysis and Management 21(1): 93-109.
• David A. Wise. 1975. "Academic Achievement and Job Performance." American Economic Review 65(3): 350-366.
• Robert W. Crandall and John D. Graham. 1989. "The Effect of Fuel Economy Standards on Automobile Safety." Journal of Law and Economics 32(1): 97-118.
• Jane Waldfogel. 1998. "Understanding the 'Family Gap' in Pay for Women with Children." Journal of Economic Perspectives 12(1): 137-156.
• Daniel S. Hamermesh and Amy M. Parker. 2005. "Beauty in the Classroom: Professors' Pulchritude and Putative Pedagogical Productivity." Economics of Education Review forthcoming.
• McKinley L. Blackburn and David Neumark. 1993. "Omitted-Ability Bias and the Increase in the Return to Schooling." Journal of Labor Economics 11(3): 521-544.
• Robert W. Fairlie and Rebecca A. London. 1997. "The effect of incremental benefit levels on births to AFDC recipients." Journal of Policy Analysis and Management 16(4): 575-597.
• James L. Mitchell. 2004. "Will empowering developers to challenge exclusionary zoning increase suburban housing choice?" Journal of Policy Analysis and Management 23(1): 119-134.
• David C. Grabowski, Michael A. Morrisey. 2004. "Gasoline prices and motor vehicle fatalities." Journal of Policy Analysis and Management 23(3): 575-593.
• Dennis Coates and Brad R. Humphreys. 1999. "The growth effects of sport franchises, stadia, and arenas." Journal of Policy Analysis and Management 18(4): 601-624.
• Ted Gayer. 2004. "The Fatality Risks of Sport-Utility Vehicles, Vans, and Pickups Relative to Cars." Journal of Risk and Uncertainty 28(2): 103-133. [click on "PDF"]
• Ian Ayres and Steven D. Levitt. 1998. "Measuring Positive Externalities from Unobservable Victim Precaution: An Empirical Analysis of Lojack." Quarterly Journal of Economics 113(1): 43-77.
• Trevor L. Brown and Matthew Potoski. 2003. "Managing contract performance: A transaction costs approach." Journal of Policy Analysis and Management 22(2): 275-297.
• Steven D. Levitt and Jack Porter. 2001. "Sample Selection in the Estimation of Air Bag and Seat Belt Effectiveness." Review of Economics and Statistics 83(4): 603-615.
• Jens Ludwig, Greg J. Duncan, and Paul Hirschfield. 2001. "Urban Poverty and Juvenile Crime: Evidence from a Randomized Housing-Mobility Experiment." Quarterly Journal of Economics 116(2): 655-679.
• Robert Bifulco, William Duncombe, and John Yinger. 2005. "Does whole-school reform boost student performance? The case of New York City." Journal of Policy Analysis and Management 24(1): 47-72.
• Brian A. Jacob and Lars Lefgren. 2004. "Remedial Education and Student Achievement: A Regression-Discontinuity Analysis." Review of Economics and Statistics 86(1): 226-244.
• Howard S. Bloom. 2003. "Using 'Short' Interrupted Time-Series Analysis To Measure The Impacts Of Whole-School Reforms: With Applications to a Study of Accelerated Schools." Evaluation Review 27(1): 3-49.
• Rajeev H. Dehejia and Sadek Wahba. 1999. "Causal Effects in Nonexperimental Studies: Reevaluating the Evaluation of Training Programs." Journal of the American Statistical Association 94(448): 1053-1062.
• Michael S. Lewis-Beck and John R. Alford. 1980. "Can Government Regulate Safety? The Coal Mine Example." American Political Science Review 74(3): 745-756.

Computer Classes

Most Fridays will be spent in the FHSS Computer Lab on the 1st floor. We will learn how to do basic and advanced statistics in Stata and basic statistics in SAS. We also will do some statistics in SPSS and Excel. This is to increase flexibility and marketability for future work opportunities. Each week, the lab will cover the commands necessary to do the weekly assignments. 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 pull-down menus, etc.).

Please arrive in the Computer Lab (112 SWKT) before class starts to start up the computer and have everything ready to go when class starts.

If you wish to purchase your own copy of Stata, the College Computing Center has set up a student license to purchase here.

Class Time

Class starts at 8:00 a.m. I realize that this is early. Please arrive on time to class so that we may end on time.

Schedule (subject to change)

Note: W=Wooldridge; K=Kennedy.

Jay Goodliffe's home page

This page is http://fhss.byu.edu/polsci/Goodliffe/504/syllabus.htm