Econometrics

Econometrics
Economics 125
Fall 2007

Course Description	Syllabus	Paper
Problem Sets	Data Sources	Normal Distribution

Course Description

Econometrics is the application of statistical techniques to economic models in an effort to achieve numerical results and to verify economic theorems. The objective of this course is to provide a very thorough presentation of important econometric concepts. Although you will not become a theoretical econometrician, you should leave the course with an understanding of the main problems which applied economists face.

The course is taught at the advanced undergraduate level for economics majors (though students in other majors are welcome). It is recommended for students interested in writing an empirical senior thesis. All students are required to have successfully studied a year of introductory economics along with a semester of statistics.

The course requirements include class attendance, five computer assignments, one midterm exam, an applied research paper and a final exam. The midterm exam will be on Thursday 18 October. The final exam will be in the evening of Monday 17 December. The computer assignments, the paper, the midterms and the final will all count for about a quarter of your course grade.

The textbook for the course is D. Gujarati, Basic Econometrics, McGraw Hill, 4th Edition, 2003. It should be available in Huntley Bookstore. Other useful references include : Studenmund, Using Econometrics, 4th edition, Addison-Wesley, 2001 and Berndt, The Practice of Econometrics, Addison-Wesley, 1991.

The computer is used extensively, but prior programming experience is not required or expected. The econometrics package we will be using is EViews. This software will be made available to students through the Pitzer Computer Network.

If any material is ever unclear, or even if everything is perfectly clear, please come chat with me about econometrics or anything for that matter. If you have a short question, please feel free to call me at the office, leave voicemail or send me email at lyamane@pitzer.edu. For longer and better explanations, come by my office duiring office hours or make an appointment to see me at your convenience. My office is in Fletcher 216 and my number is 607-3769. Office hours for the fall will be on Mondays from 3:30-5:00pm and Wednesdays from 8:30-10am and by appointment.

Course Syllabus

I. Introduction to Regression Analysis Ch 1
II. Two Variable Regression Model Ch 2
     A. Estimation Ch 3
     B. The Classical Model Ch 4
     C. Hypothesis Testing Ch 5
     D. Extensions Ch 6
III. Multiple Regression Analysis
     A. Estimation Ch 7
     B. Inference Ch 8
IV. Dummy Variables Ch 9
V. Extensions of the Basic Regression Model
      A. Multicolinearity Ch 10
      B. Heteroskedasticity Ch 11
      C. Serial Correlation Ch 12
      D. Specification Error Ch 13
VI. Special Topics
     A. Limited Dependent and Qualitative Variables Ch 15
     B. Simultaneous Equations Models Ch 18
          1. Identification Ch 19
          2. Estimation Ch 20
                 a. Direct Least Squares
                 b. Indirect Least Squares
                 c. Instrumental Variables
                 d. Two Stage Least Squares
                 e. Three Stage Least Squares
                 f. Full Information Maximum Likelihood
     C. Time Series Econometrics Ch 21