ECO 582
Fall 2015
Computational Econometrics
Instructor:
Shaowen Wu
Office:
421 Fronczak Hall
Email:
sw15@buffalo.edu
Course Webpage:
Tel:
645-8673
https://ublearns.buffalo.edu/index.html
Office Hours: W 3:00 - 4:30 p.m. or by appointment
Course Objectives
This course focuses on how to apply standard econometric techniques to different types
of real world data. The statistical package SAS will be used to give students unique
experience handling economics and finance data. Students will learn how to use SAS
through intensive hands-on computer assignments throughout the course. Students who
master the course material will acquire the statistical knowledge and computing skills
analyzing real world problems.
Recommended Text Books
Wooldridge, J. (2006), Introductory Econometrics: A Modern Approach, 3rd Edition,
South-Western.
Stock, J. and M. W. Watson (2003), Introduction to Econometrics, Addison-Wesley.
Grading Policy
1. Lab Assignments (40%)
2. Final Lab and Test (60%): TBA, Park 450.
During each lab session you need to perform a set of required tasks. By the end of the
session, you need to submit the results as instructed to get the credit. Late submissions
are in general not allowed. Sometimes, there will be optional tasks in the lab sessions.
They are for your further practice.
There will be approximately one lab each week. The lab descriptions will be announced
on UB Learns ahead of time. You should check for other announcements on UB Learns
from time to time as well. One has to attend the lab sessions to earn the credits of the lab
assignments. If you don’t show up for the lab session, the TA would not grade your
submission.
There will be no make-ups for the final lab and exam. If you miss either of them, you
will receive a score of 0 for it. If you have a legitimate reason to miss them, like a
doctor’s note, you would get an Incomplete with a default grade calculated based on a
zero score for the missed exam. You then need to arrange with the instructor to reach a
way how to make up for it. There are two possibilities: take a make-up exam on a
mutually agreed date at the beginning of the spring semester or take the exam offered in
the same course next fall semester.
Incomplete grade would not be assigned except in the case that the students miss the final
lab or exam with a legitimate reason. Please refer to the university Incomplete Policy if
necessary.
Accessibility Resources
Please visit UB's Accessibility Resources Office for accessibility resources the
requirement to register with that office in order to receive accommodation for physical
and learning disabilities.
Academic Integrity
In strict accordance with the University Policy any violations to the Academic Honesty
Code will be reported to the chair of Economics Department. Whatever verdict the Chair
gives will be implemented.
Tentative Lecture Schedule
1. Review of Probability Theory and Mathematical Statistics, Data Description, and
Software Overview
2. Introduction to SAS and Data procession
3. Introduction to the Basic Regression Model
4. Statistical Inference and Forecasting in OLS
5. Scale, Demean, Detrend, Deseasonlization, and Multicollinearity in OLS
6. Specification in OLS: Serial Correlation and Heteroskedasticity
7. Functional Form, Nonnormality, Structural Break, Model Selection, etc.
8. Probit and Logit Models
9. Classical Time Series Models
10. Advanced Time Series Models and Forecasting
11. Panel Data Analysis
12. Simultaneous Equation Models
Good luck and enjoy the course!