...

ECON 7818-001 Econometrics I

by user

on
Category: Documents
2

views

Report

Comments

Transcript

ECON 7818-001 Econometrics I
ECON 7818 Syllabus
Graduate Econometrics Seminar
Fall 2002
Professor: Jose J. Canals-Cerda.
Office: Econ 103
Phone/Voicemail: 303-492-7869
E-mail: [email protected]
Class meets on Tuesday and Thursday 12:30 p.m. to 1:45 p.m.
Classroom: Econ 11 7
(The information in this syllabus is subject to change).
Course Objectives.
The course is designed as a rigorous introduction to advanced statistics and
econometrics.
Additional Information.
Please send me a brief email message containing your name and with the
subject "ECON7818 Student". Be aware that most of the course
announcements will be done using e-mail. Therefore, it is important that you
send this email to me as soon as possible.
How to contact me.
Office Hours: My office hours are Tuesdays and Thursays from 11 :00 a.m.
to 12:00 p.m. I will be in my office Tuesdays and Thursays most of the day,
you can talk to me these days at any time if I am available. At any other
time, it is best if you make an appointment (by e-mail or phone).
Students with Disabilities.
This University abides by Section 504 of the Rehabilitation Act of 1973,
which stipulates that no student shall be denied the benefits of an education
"solely by reason of a handicap." Disabilities covered by law include but are
not limited to learning disabilities and hearing, sight or mobility
impairments. If you have specific physical, psychiatric, or learning
disabilities and require accommodations, please let me know early in the
semester so that your learning needs may be appropriately met. You will
need to provide documentation of your disability to the Disability Services
Office in Willard 322 (phone 303-492-8671).
The course paper. ·
One of the requirements of this class is a paper. The course paper will
replicate published research. This work will require the use of statistical or
econometrics computer packages. You are not required to use a specific
package. You can access computer packages like LIMDEP, GAUSS or SAS.
You can buy some of this products and additional ones, like STATA or
SAS, from the University at a reasonable student price. During the semester
we will spend some time teaching SAS. You should plan to get started on
your paper as soon as possible. You may be required to present the paper in
class. The quality of your presentation will be an important determinant of
your grade, this applies also to the programs. The final draft of the paper will
consist of an introduction describing and motivating the interest of the paper
in a simple way, as well as a road map with a short description of the
different sections of your paper. The paper should have a section describing
the data, a section describing the econometric methodology, a section with
results and a final section presenting the conclusions. If necessary, the paper
may include one or several appendixes. In particular, the programs used for
the statistical work should be included in an appendix.
Quizes and Exams.
There will be several quizes administered during the semester and one final
exam. I will also provide you with problem sets but they will not be graded.
I encourage you to work in groups.
Grading.
The grade for this class is based on your performance in quizes, a final
exam, the research proposal and the research paper.
Quizes: 20%
Final Exam: 50%
Research Paper: 25%
Texts and Other Materials.
Recommended books:
Rice, John A. : "Mathematical Statistics and Data Analysis." Wadsworth &
Brooks/Cole Advanced Books & Software Pacific Grove, California.
Amemiya, Takeshi (1994): "Introduction to Statistics and Econometrics."
Harvard University Press.
Cody and Smith: "Applied Statistics and the SAS Programming Language."
Prentice Hall Ed. (4th edition). (This is a book for learning sas).
Course Outline.
What follows represent a tentative list of subjects to be covered in class.
Introduction to Regression analysis.
Introduction to regression analysis. Omitted variables. Endogeneity. Linear
probability model.
Probability Theory.
Introduction. Axioms of Probability. Conditional Probability and
Independence.
Random variables and probability distributions.
Definitions. Discrete Random Variables. Continuous Random
Variables. Distribution Function. Change of Variables. Normal Random
Distribution.
Moments.
Expected Value. Higher Moments. The Moment Generating Function.
Covariance and Correlation. Conditional Mean and Variance.
Large sample theory
Modes of convergence. Laws of Large Numbers and Central Limit
Theorems.
Point Estimation
Introduction. Properties of Estimators. Least Squares Estimators.
Maximum Likelihood Estimation and Method of moments
estimation.
Introduction. Properties of Maximum Likelihood and Method of Moments
Estimation.
Interval Estimation and Test of Hypothesis.
Introduction. Confidence Intervals. Test of Hypothesis. Constrained Least
Squares Estimators. Test of Hypothesis in the Linear Regression Framework.
Advanced econometric models.
Generalized Least Square. Nonlinear Regression model. Qualitative
Response Models.
Fly UP