EC 570 Econometrics
Course Syllabus
Fall 2006, 4:40 - 6:30pm TTH (CH 296)
Prof. K.-P. Lin (CH 241G, 725-3931)
Office Hours: 4:00-4:30 TTH & by appointment
This series of graduate level econometrics courses is designed to teach students with basic
quantitative and computer skills for economic modeling, analysis and application. This course
discusses basic econometric techniques and applications, while the next sequence EC 571
covers more advanced topics.
Prerequisites
EC 370 Introduction to Quantitative Economics provides the quantitative fundamentals for this
courses. Basic knowledge of calculus, matrix algebra, statistical inference and probability theory
are required (e.g., MTH 251, 252, 261; STAT 243, 244).
Texts
- Required:
- F. Hayashi,
Econometrics, Princeton University Press, 2000.
- Recommended:
- W. H. Greene,
Econometric Analysis, 5th ed., Prentice Hall, 2002.
- C. F. Braum,
An Introduction to Modern Econometrics Using Stata, Stata Press, 2006.
- K.-P. Lin,
Computational Econometrics: GAUSS Programming for Econometricians and Financial Analysts,
ETEXT Publishing, 2001.
Software: Stata or GAUSS
Both Stata and GAUSS are available in the Economics Lab (CH-230).
- Stata 9, StataCorp, 2005.
A version of Small Stata may be used for the class.
- GAUSS 7, Aptech Systems, 2006.
A version of GAUSS Light may be used for the class.
- GPE2 for GAUSS, included in Computational Econometrics.
Free download of GPE2 for GAUSS 7.0 and GAUSS Light are available
here for registered students only.
Course Topics
- Least Squares Estimation
- Small Sample Theory
- Large Sample Theory
- Instrumental Variables
- Generalized Method of Moments
Lecture Notes based on Hayashi (2000):
Chapter 1a,
Chapter 1b,
Chapter 1c,
Chapter 1d,
Chapter 1e,
Chapter 1f,
Chapter 2a,
Chapter 2b,
Chapter 2c,
Chapter 2d,
Chapter 2e,
Chapter 3a,
Chapter 3b,
Chapter 3c,
Chapter 3d,
Chapter 3e,
...
Sample example programs (Stata):
nerlove1.do,
nerlove2.do,
nerlove3.do,
mishkin1.do,
mishkin2.do
mishkin3.do,
grilic.dta,
grilic1.do,
grilic2.do
grilic3.do,
...
Sample example programs (GAUSS):
nerlove.1,
nerlove.2,
nerlove.3,
mishkin.1,
mishkin.2,
mishkin.3,
grilic.dat,
grilic.1,
grilic.2,
grilic.3,
...
Course Expectation
For this course, there are two (2) tests: midterm and final. In
addition, there are 4-5 homeworks (once every two weeks in average). Also there is a course project
due at the end of term. The time schedule and grade distribution are as follows:
| Midterm | November 2 (Thursday), in class | (30%) |
| Final | December 5 (Tuesday), 5:30pm | (30%) |
| Project | December 5 (Tuesday) | (20%) |
| Homework | Due every 2 weeks | (20%) |
Homeworks
Guideline on Writing a Course Project
Format
- 5-10 pages typed (double-space and wide margins).
- The model presented has to be an original econometric model.
- The format of the paper should follow a standard journal article closely.
- Supporting data and computer program printout have to be included, but not counted
for the page number.
Contents
- Introduction and brief discussion of the main results.
- Full explanation of estimation, hypothesis testings, and model specifications.
- Detailed interpretation of the model and its policy implication, if any.
- Extensions could be taken up in EC 571 next term.
- References (including data sources).
Grade and Deadlines
- The project is evaluated based on its originality, creativity, and consistency with
the format and content requirements described above.
- Project proposal (1 page typed): November 9 or earlier.
- Project due: December 5 (Tuesday).
Useful Econometrics Resources and Data Sources
Copyright©
Kuan-Pin Lin
(Last updated: 11/07/06)