Econometrics
II
Econ 620
Instructor: Nicholas M. Kiefer (nmk1)
Cornell University
Department of Economics
Spring 2008
Introduction 
This
course deals with estimation and inference using economic models and economic
data. We will cover the linear regression model and variations that arise
when "ideal" conditions are not met. We will also cover, at the
introductory level, maximum likelihood estimation, nonlinear models and
simultaneous equation models. We rely heavily on lecture notes. These are
available from the course web page : http://instruct1.cit.cornell.edu/courses/econ620
and lecture notes should be read in advance of the lectures. 
Text
Books 
A
good econometrics text is a valuable supplement: consider Judge et al Theory
and Practice of Econometrics, 
Paper 
A
short (10 pages) paper reporting an application of econometrics is required.
You may use any economic data sets. CISER is a potential source of data. Also
check the business library. A project proposal of 1~2 pages (ideally 1 page) describing the
question you will be looking at, the data you will use, and the relevant references
to the literature must be submitted for approval by 2/14; it is to your advantage to
do this as soon as possible. Preliminary
results will be presented to the class with the aid of handouts or
transparencies beginning after the break. You will have 20 minutes for
presentation  this is about the time allocated at the ES/AEA winter meetings
and the ASA August meetings. You should plan to present at these meetings
when you are on the job market and you might as well start practicing now.
Have fun with these projects; this is
what you are preparing to do for the rest of your careers. The final version
of the paper is due at the end
of classes (last lecture, that is, 5/1). 
Grades 
Grades
will be based on the paper (35%), a midterm (20%), a cumulative final (35%),
and on promptness in turning problem sets, the quality of your presentation,
and participation in class discussion during the student presentations (10%).
Failure to meet deadlines in turning in the proposal or the papers will be
penalized heavily. 
Midterm 
The
midterm will cover the first 14 lectures; the material required is thorough
knowledge of the linear regression model, including GLS, and asymptotics at the level covered in class and notes. The
midterm will occur on 3/13. 

I
encourage you to work together on problems and on the programming required
for the projects. 