ECON 452 (A & B) Winter 2001 C. Ferrall / A. Gregory

SYLLABUS

Please take note of changes in red concerning Part II made during Reading Week.



CONTACTS

 
Instructor Part I
Instructor Part II
Teaching Assistant
Name Prof. Allan W. Gregory Prof. Chris Ferrall Jason Hwang
Office MC A424 MC A519 MC A504
Hours Wed 10:00-12:00 
Thur  08:30-10:00 
by appointment 
Wed 11-12
Thur 11-12 &
by appointment
Mon 4:00 – 5:30 
Tue 3:30 – 5:00
(in Dunning 350)
Phone 533-2299 533-6658 On-Campus: 74030


Off-Campus: 533-6000x74030

E-mail  awg@qed ferrall@qed hwangj@qed
 
@qed is short for @qed.econ.queensu.ca

 
 
 
 

OBJECTIVES

Description from the A&S Calendar:

  .


The description above was written many years ago and has not been updated.  Despite this heritage it is surprisingly accurate, but a more precise and detailed discussion of our specific objectives is warranted.:

Part I

In Economics 351, you studied the classical linear regression model. One key assumption of this model was a fixed X (non-stochastic regressors). For time series models, this assumption is untenable. Researchers are now compelled to understand the econometrics of time dependent processes. While the tools of classical econometrics are extremely useful in advancing in this direction, there are many important departures in time series that require additional machinery.

The intention of Part I is to learn and to use the tools of applied time series analysis. This modelling technique is atheoretical.

Our emphasis will be on application; that is, taking the concepts developed in the lectures and employing them in two time series projects. However, there will inevitably be a great deal of theory in the lectures given the nature of the topic.

Notes are bound and sold to you at cost from the AMS Publishing office.These notes are intended to serve as the basis of all the theory. No other book is required.

Part II

As with part one, Economics 351 is our departure point.  The first project gives you the opportunity to learn by doing the first steps in the art and practice of applied micro-econometrics.


The second project in Part II gives you the opportunity to learn by doing the most important class of statistical model beyond multiple regression for analyzing survey data sets, namely limited dependent variable (LDV) models of various sorts (logit, probit, and tobit).  The same process is required in the second project as the first, but now much more attention is paid to applying techniques appropriately and correctly interpreting the results.
 
 

SCHEDULE

Part I: the first six weeks of both sections, taught by Professor Gregory.


Part II: the second six weeks of both sections, taught by Professor Ferrall.
 

REQUIRED MATERIAL

MARKING

The good news: no exam. The bad news: no exam. Your mark will be solely based on four projects (20 % each) and in-class work (20%) described below. This is a very demanding course and as a warning the workload is above average. We hope the potential for independent work and learning will be a sufficient reward to compensate for the long hours spent.  Besides long hours, you should expect a fair amount of frustration during the process of learning new statistical techniques and computer programs, handling real-world data, and writing your results in a format suitable for busy people to understand and appreciate your work.  This many hours of apparently unproductive work getting the computer to do what you want it to do is simply the first unavoidable stage to becoming an applied econometrician. We have spent many hours ourselves trying to smooth this process for you as a student (and to avoid many mindless tasks we had to perform when we were students).  But there is no guarantee that our software will work perfectly.  It is your responsibility to seek help when problems or confusion occurs in time to meet the assignment deadlines.

 
 
Summary of Course Work and Marking Policies

Part
Title
Due Date
Weight in final mark
I
Summarizing an Empirical Paper
  October 5
20%
 
Box-Jenkins Identification and Estimation
 October 29
20%
 
In-class Exercises and Participation 
2nd lecture each week
|10%
  Notes: Each project should be no longer than 10 typed double spaced pages. These projects are viewed as separate two or three week assignments, and the deadline is taken as given. No exceptions. In the second half of the second weekly lecture (For Section A -Wednesday and Section B- Thursday), I will give you some time series exercise to do on the computer using the built-in STATA programs or the ones I have written. The real intention here is to help you get familiar with the STATA code so that you can do your projects.

At the end of 6 weeks, I will make an overall assessment of this work, as well as your efforts in class and assign a grade out of 10. These weekly in-class assignments are marked gently and much of the grade is awarded simply for giving it the old college try.
 

 
II
Multiple Linear Regression on Survey Data
Sunday, March 25
20%
  Estimation of a Limited-Dependent Variable Model
Sunday, April 15
20%
  In-class Exercises and Participation
each class
10%
  Notes:
Each project should be no longer than 10 typed double-spaced pages, excluding tables and appendices. Projects must be posted on the students' qlink WWW homepage in either HTML or as Microsoft Word document (save as Word 97) as a PDF or HTML file by midnight of the due date and not modified thereafter.  No exceptions.

Each project MUST be done in groups of two or three. Partners can be from both sections, and they can be different for each assignment. (Prior approval for a solo project is possible only with an explanation.)

The in-class mark will be a function of student performance on in-class exercises and general level of constructive participation in class.  This includes not only asking and answering questions, but also politiely listening to other students, pointing out problems or confusions in material, etc.

 
  Total
100%



[Econ 452 Homepage][Course Outline]