Temple University
Department of Economics
Economics 615 Econometrics I
Fall 2001
Speakman Room 212
Wednesday 7:25 PM - 9:55 PM
Information for an electronic age: | Send me email: Andrew J. Buck |
Call me: 215-204-1985 FAX me: 215-204-8173 |
Visit me: |
813 Ritter Annex Any time on Wednesday |
Texts and other materials:
Econometric Analysis, 4th Ed., William H. Greene, Prentice-Hall, 2000.
This book is the most widely used text in U..S. grad programs. It will
challenge you every step of the way, but it is well worth the investment in time and
money. The fourth edition is not much changed from the third. However, the
fourth edition has a CD with the data sets from the text and an abbreviated version of
LIMDEP, Greene's statistical software package. BUY THE 4TH EDITION.
Optional (If you can find a copy): Basic Econometrics, 3rd Ed., Damodar Gujarati, McGraw-Hill, 1995.
Gujarati's book is a nice undergraduate treatment of econometrics. It is short on
theory and has many numerical examples; as such it makes good background reading for
Greene.
The syllabus has many links to the lecture notes which I have written over the years. The lecture notes are meant to be read along with the text for the course. In addition I have links to a set of lecture notes prepared by Douglas J. Miller (Ph.D., Berkeley, 1994), Assistant Professor of Economics, Iowa State University. His excellent lecture notes are more advanced than my own.
There is an index to other courses notes available online. The files are predominantly in *.pdf and so your computer is nothing more than an electronic page turner.
Links to some graphic JAVA applets to aid your understanding.
Rules of the Game:
Attendance is at your discretion, but I have not met anyone who can do well in graduate school without a near religious commitment to the course of study. You should read the assignments before coming to class. This applies even if you feel that we are way behind schedule or that your are better prepared than the other students in the class. As in all of your classes, the subject is cumulative. Sometimes an earlier discussion will become clearer by having read material which comes after it. Our time in class is brief. To make the most of that class time you should write out your questions and bring them with you; you should quiz yourself on what you have read; you should get together in study groups and quiz one another. If you haven't already heard, this class is demanding. Come to class prepared and don't fall behind. You can read some more about where we are headed with 615 and 616.
Course Grade Determination:
Homework 25%
Midterm 25%
Final 25%
Paper 25%
Homework: To discourage late homework, it is accepted at only 50% of the lowest score earned by those who turned it in on time. The PhD is a research degree. When you are done you are certified as having the ability to conceptualize, research and solve problems in economics. The practical consequence of this is that you may have to do some research in order to do your homework. This semester I have drawn the homework assignments from similar courses offered at other universities. This should give you some idea of what your peers are doing around the world.
Paper: You will note in the syllabus that there are some interim products which must be produced as part of your research paper. If you do not submit the interim products then I will not accept the paper. You must turn in a diskette with your data and regression programs. A late paper will automatically receive a grade no higher than a 90%.
Exams: The midterm will cover all material to that point. It is mandatory. The final is cumulative and mandatory. Only a note from an MD will be accepted for missing an exam. The date for the final is included in the syllabus, make your travel plans accordingly.
Syllabus: The following table will provide you
with a schedule for homework, reading and exams. Econometrics is not the sort of subject
that can be left for a last minute cram. It takes a continuous level of effort.
Date | Topic | Reading | Sample Hwks | Hwk for Fall 2001 |
Aug 29 | Descriptive Statistics and Probability | Greene, Chap 3 | ||
Sept 5 | Random Variables and Distributions | Greene, Chap 3 | Paper Title | |
Sept 12 | Sampling Distributions and Estimation | Greene, Chap 4 | Homework 1: Desc Stats, Prob and
R.V.s Paper Abstract - Statement of Problem |
Probability and RV's: Part I |
Sept 19 | Hypothesis Testing, Small Sample and Large Sample | Greene, Chap 4, Miller L15 | Hwk 2: Sampling Answer Key |
Probability and
RV's: Part II
Answer Key |
Sept 26 | Analysis of Variance | Hwk 3: Intro to
Statistical Inference Answer Key |
Inference
Answer Key |
|
Oct 3 | Simple Regression, MVNB: Simple Regression | |||
October 10 | Mid-term Exam and Answer Key from 1999. | Hwk 4: Simple Regression | Simple Regression | |
October 17 | Matrix Algebra | Greene, Chap 2 | Annotated Bibliography | |
October 24 | Multiple Regression: OLS, RLS and their Properties, An Application | Greene, Chap 6; Miller L1, L2, L3 | ||
October 31 | Multiple Regression: Gauss-Markov and GLS | Greene, Chap 6 | Hwk 5: OLS Computations, Answer Key |
|
November 7 | Hypothesis Testing:t-tests, F-tests, large sample tests | Greene, Chap 7; Miller L9, L16, L17 | Detailed Outline | Multiple Regression |
November 14 | Data Problems: Misspecification, Missing Data, Multicollinearity | Greene, Chap 9; MillerL8 | Hwk 6: Bread and Meat: Data Answer Key |
Gauss Markov |
November 28 | Heteroscedasticity | Greene, Chap 12 | Hypothesis Testing
Answers to the first question of this problem set. |
|
December 5 | Autocorrelation | Greene, Chap 13 | Hwk 7: Almon Lags, Data Answer Key |
Heteroscedasticity |
December 12 | Final Exam
Key Fall 2001 |
Paper, Hwk 8: Autocorrelation and data, Answer Key |
Autocorrelation |
To get the set of MathCAD documents I have been using in class click for the self-extracting file.