Temple University
Spring 2011
Economics 3503
Econometrics
MWF, 11:00 AM - 11:50 AM
Ritter Hall 101
Textbook: Introductory Econometrics: A Modern Approach, 4th Edition, Jeffrey Wooldridge, Southwestern.
Please scroll down to the material at the bottom of the syllabus for information about course and university policies, contact information, textbook and grading.
Date (week of) | Topic | Text | Homework |
January 19 and January 21 | Statistical Boot Camp: What you should know, but which I know you have forgotten! | Chapter 1 Appendix A Basic Mathematical Tools. |
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January 24, 26 and 28 | Same as above | ||
January 31, February 2 and February 4 Monday, January 31, Last Day to Drop |
Simple Linear Regression Model | Wooldridge: Chapter 2 CEO Salaries |
First Homework due February 4 Answer Key |
February 7, February 9 and February 11 | Interval Estimation and Hypothesis Testing | Wooldridge: Chapter 2 | |
February 14 and February 16 | Prediction, Goodness of fit and modeling issues | Wooldridge: Chapter 2 | Hwk: Simple OLS due February 16 Answer Key |
February 18, Friday, First mid-term exam |
Exam 1 |
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February 21, February 23 and February 25 | Multiple Regression Model: Estimation | Wooldridge: Chapter 3 | Hwk: Hypothesis Testing due February 25 Answer Key |
February 28, March 2 and March 4 | Multiple Regression: Estimation & Inference | Chapter 3 & 4 | Hwk: Rescaling Variables due February 28 Answer Key |
March 7, March 9 and March 11 |
Spring Break |
Paper Assignments |
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March 14, March16 and March 18 | Multiple Regression: Inference | Chapter 4 Outline |
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March 21, 23, 25 | Multiple Regression: Further Issues | Chapter 6 Notes | Hwk: Hypothesis Testing R&D Data Student Rental Charges This homework is due on March 25. Get the Answer Key. |
March 28, Monday, Second mid-term exam |
Exam 2 |
2011 Exam Key | |
March 29, Last Day to Withdraw March 30 and April 1 |
Regression with Qualitative Independent Variables | Chapter 7 |
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April 4, April 6 and April 8 | Heteroscedasticity | Chapter 8 & 9 Outline |
Dummy Variables Homework Due April 8 GPA dataset GPA data description Answer Key |
April 11, 13 and 15 | Basic Regression with Time Series Data | Chapter 10 & 12.1 through 12.5 Notes, which actually include a wee bit of material from Chapter 11 as well. |
Heteroscedasticity Homework Due April 15 Answer Key House price dataset House price data description |
April 18, 20 and 22 | Simultaneous Equations Models and IV Estimation | Chapters 15 and 16 Notes | Time Series issues and Autocorrelation Homework Due April 22 Answer Key Traffic dataset Traffic Data Description |
April 25, 27 and 29 | Simultaneous Equations Hwk Due April 29 Get the key here. Cigarettes and Income data Data description |
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Monday May 2 | Your paper is due today! |
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Friday, May 6, |
Final Exam -- 10:30 - 12:30 AM |
2011 exam key |
Textbook:
Jeffrey Wooldridge, Introductory Econometrics: A Modern Approach, 4th Edition, South-
Western, Cengage Learning. ISBN10: 0324581629 ISBN13: 9780324581621
Office Hours
831 Ritter Annex, MWF, 2 PM - 3:30 PM
You can always reach me by email: buck at temple.edu. Or try the telephone -- 215-204-1985
Course rationale, objective and theme:
What separates economics from most other social sciences is that our discipline begins with a few
basic assumptions and utilizes these as building blocks for extensive models of the real world.
Models are only useful if they can be tested with data and economists have developed extensive
statistical models that are used to test their theories. The workhorse statistical model in the social
sciences is the ordinary least squares (OLS) regression. The bulk of the course will be outlining
the theory behind and the properties of the OLS model. The course will however not just be an
abstract exercise. For each topic, I will first present a standard textbook treatment of the topic. I will provide sample data that
illustrates how one would obtain estimates given appropriate data.
The class will use the EVIEWS statistical software package. EVIEWS is a fast and versatile
program that was written by economists so it is more intuitive for people in our field. EViews is available in Anderson Hall computer lab. Knowledge of EVIEWS will greatly
enhance your ability to get a job after graduation.
Prerequisites:
Economics 1101 and 1102 and Statistics 2101 and 2102 (or the equivalent). No matter what your background or your sense of your own abilities, students should take a statistics course before taking econometrics. You are also expected to
know some simple calculus.
I have put on the syllabus a 20 page review of the necessary background statistics.
This handout goes over most of the important concepts that will be used this semester such as
expected values, covariance, correlation, linear combinations of random variables, test of
hypothesis, testing the equality of means from two samples, etc.
Expectations:
Students are expected to attend class, be prepared for class, to NOT be late to class, to participate in classroom discussions, to hand in assignments when due, and to NOT engage in academic dishonesty.
COURSE WORK:
There will be three tests, all closed book (no formula sheets or flashcards will be allowed on the tests). The tests will only include materials covered in class; problems and questions will be similar to those in homework assignments. No makeup tests will be given. There will also be regular homework assignments posted on the syllabus. You will have to turn in handwritten assignments on dates given in the syllabus. They will be graded. When solving homework or test problems, please show all your work; mere answers will earn no credit. Your answers must be strictly individual (copying from a classmate may involve a disciplinary action). If you are not going to be in class, please fax or e-mail your assignment to me as a Word attachment before the deadline. No late submission will be accepted (because I put all the answers on the web site).
GRADE: The following weights will be applied for the purpose of determining the course grade:
Exams 3 x 20 = 60
Homework 20
Paper 15
Attendance and class participation 5
Total 100%
Your grade will be based solely on performance, and there will be no extra work for missed credit. I give all grades, from A to F. The class is math intensive and will be boring if you hate math. Homework assignments are hard, especially in the second part, when you will study new materials that were not covered in statistics courses. Attendance is crucial!
Academic Freedom, Rights and Responsibilities: Freedom to teach and freedom to learn are inseparable facets of academic freedom. The University has adopted a policy on Student and Faculty Academic Rights and Responsibilities (Policy # 03.70.02) which can be accessed through the following link: http://policies.temple.edu/getdoc.asp?policy_no=03.70.02.
Disability Statement: This course is open to all students who meet the academic requirements for participation. Any student who has a need for accommodation based on the impact of a disability should contact the instructor privately to discuss the specific situation as soon as possible. Contact Disability Resources and Services at 215-204-1280 in 100 Ritter Annex to coordinate reasonable accommodations for students with documented disabilities.
Policy on Cell Phones: Cell phones, pagers and beepers must be turned off during class except with special permission from your instructor.
Attendance Policy: As you can see from the Class Participation and Course Grading Formulas, attendance is very important to your success in this class. Absence due to illness still means that you are not participating in class If you are sick, you will need to provide a note from the doctor. Students with an emergency (e.g., death in the family, illness, automobile accident) may have an excused absence, but if such absences amount to more than 20% of class hours for the semester, students should consider the possibility of withdrawal from the class.
Plagiarism and Cheating: Temple University believes strongly in academic honesty and integrity. Plagiarism and academic cheating are, therefore, prohibited. Essential to intellectual growth is the development of independent thought and a respect for the thoughts of others. The prohibition against plagiarism and cheating is intended to foster this independence and respect.
Plagiarism is the unacknowledged use of another person's labor, another person's ideas, another person's words, another person's assistance. Normally, all work done for courses -- papers, examinations, homework exercises, laboratory reports, oral presentations -- is expected to be the individual effort of the student presenting the work. Any assistance must be reported to the instructor. If the work has entailed consulting other resources -- journals, books, or other media -- these resources must be cited in a manner appropriate to the course. It is the instructor's responsibility to indicate the appropriate manner of citation. Everything used from other sources -- suggestions for organization of ideas, ideas themselves, or actual language -- must be cited. Failure to cite borrowed material constitutes plagiarism. Undocumented use of materials from the World Wide Web is plagiarism.
Academic cheating is, generally, the thwarting or breaking of the general rules of academic work or the specific rules of the individual courses. It includes falsifying data; submitting, without the instructor's approval, work in one course which was done for another; helping others to plagiarize or cheat from one's own or another's work; or actually doing the work of another person.
Students must assume that all graded assignments, quizzes, and tests are to be completed individually unless otherwise noted in writing in this syllabus. I reserve the right to refer any cases of suspected plagiarism or cheating to the University Disciplinary Committee; I also reserve the right to assign a grade of "F" for the given paper, quiz or test.