Econometrics (26:223:554:01)
Fall 2002
Professor Robert H. Patrick
Department of Finance and Economics
Rutgers Business School - Newark and New Brunswick
Econometrics will meet Thursdays, 10 AM-12:50 P.M., in the
Global Financial Market Center (GFMC), Ackerson Hall, Newark Campus
Offices and hours: Janice Levin Building 129, Livingston Campus, Wednesdays 4:30-5:30 P.M.,
Ackerson Hall 312, Newark Campus, Thursdays 1:15-2:15 P.M., and by appointment.
Phone: (973) 353-5247, however, communication by e-mail is preferred outside of office hours.
(732) 445-3234, but only during my Wednesdays office hours.
e-mail: rpatrick@andromeda.rutgers.edu
web: http://www.rci.rutgers.edu/~rpatrick/hp.html
The purpose of this course is to develop basic econometric estimation and hypothesis testing tools
necessary to analyze and interpret the empirical relevance of financial and other economic data. This
requires developing statistical methods for estimation of population parameters and testing hypotheses
about them using a sample of data drawn from the population distribution, under various assumptions
regarding the true population relationship between the observable economic variables. The course will
focus on the theoretical foundations of econometric analysis and strategies for applying these basic
econometric methods in empirical finance and economics research. The course will cover estimation
and hypothesis testing using the classic general linear regression model, combining sample and
nonsample information, dummy variables, random coefficients, multicollinearity, and the basics of large
sample theory, nonspherical disturbances, panel data, systems of equations, time-series, and their
application.
There are a number of very good econometric software packages available. SAS (Rutgers has a site
license) and LIMDEP (a student version comes with the Greene text referenced below) are two such
packages that are widely used and will be briefly introduced in this course. While no specific software
package is required for computations necessary to complete this course, the use of some computational
software will be required to complete the requirements in this course.
The statistical methods covered in this course are a continuation and generalization of the material
covered in Linear Statistical Models (26:960:577). The references will serve as your background
material for the topics listed below. Students are encouraged to seek out whatever reference material
facilitates their learning of each topic. For example, the topics in Griffiths, Hill, and Judge are also
covered in Greene, but Greene presents a more concise and mathematical treatment. Related empirical
articles from the economics and finance literature will also be assigned, as well as selected material from
the books listed as references below.
Course References
*
William Griffiths, R. Carter Hill, and George G. Judge, Learning and Practicing Econometrics,
John Wiley and Sons, Inc., 1993.
*
W.H. Greene, Econometric Analysis 5th Edition, New Jersey: Prentice Hall, 2002.
*
R. Carter Hill, LEARNING SAS: A Computer Handbook for Econometrics, John Wiley and Sons,
Inc., 1993.
Handbook of Econometrics Volumes I-IV, North-Holland, various years.
Handbook of Applied Econometrics Volumes I and II, Basil-Blackwell, various years.
John Campbell, Andrew Lo, and A. Craig MacKinlay, The Econometrics of Financial Markets,
Princeton University Press, 1997.
* these books should be available in the bookstore. All of these books should be available in the library.
Anticipated Schedule:
Topics
Date
Introduction, Classical General Linear Regression Model
Sept. 5
Sept. 12
Introduction to the GFMC and econometric software (SAS, LIMDEP)
Classical General Linear Regression Model (continued)
Sept. 19
Inference & Testing Hypotheses
Sept. 26
Combining Sample and Nonsample Information
Oct. 3
Dummy Variables and Random Coefficients
Oct. 10
Multicollinearity
Oct. 17
Large Sample Theory
Oct. 24
Nonspherical Disturbances
Oct. 31
Nonspherical Disturbances continued
Nov. 7
Introduction to Panel Data Models
Nov. 14
Introduction to Systems of Equations
Nov. 21
Introduction to Time Series
Dec. 5
Applications
Dec. 12
Course Review
Final Exam
Other topics may be added as time permits.
Evaluation of performance: Students are responsible for all problems and problem sets assigned in
class, which will be randomly collected and graded. Quizzes, graded problems and problem sets, and
class participation will comprise 50% of your grade, and the final exam the other 50%.