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							Cal Poly Pomona, Fall 2008                                 Office: 1-339; Phone: (909) 869-5074
Professor: Bruce Brown                                     email: bbrown@csupomona.edu

                 ECONOMICS 421/421A - Introduction to Econometric Methods
       Tu 1-3:50 (1-2:50 in lab, 1-317; 3-3:50 in room 9-283 for quizzes); Th 1-2:50 in 7-203

Brief Course Description:
    Econometrics can be considered regression analysis with emphasis on issues, problems, and
techniques of particular importance when using non-experimental data typically used by economists.
This course introduces econometrics in an applied and applications oriented manner. It includes
quantitative model building, verification, and prediction of economic variables. A general statistics
course is a required prerequisite (e.g., EC322/322A at Cal Poly). Recommended prerequisites include
basic mathematics as applied to economics (EC406), and intermediate economic theory (EC401, EC402,
and EC403). Students with a less extensive background in economics should expect to devote more time
and effort to the class in order to compensate. Most students will need to read material more than once to
truly understand it. Actively solving problem sets and completing computer assignments which involve
“hands-on” implementation of regression techniques are essential to this course.

Course Objectives:
i) Understand the intuition behind the procedures involved in regression analysis.
ii) Gain basic proficiency in implementing and interpreting regression models in an economic context.
iii) Gain familiarity with a) statistical support for econometric methods; b) required assumptions;
    c) ways in which these assumptions may be violated; and d) techniques to use, and changes in
    conclusions when assumptions don’t hold.
iv) Ability to use appropriate statistical software such as Excel and EViews.
v) Practice in presenting empirical results which include regression analysis.
vi) Experience in evaluating empirical arguments contained reports, studies and presentations.

Required Material:
- Text: Using Econometrics – A Practical Guide, 5th edition, by A.H. Studenmund.
   (realize this is similar to the 4th edition)
- Software: EViews – Students will not be required to purchase (it is available in the lab, 1-317)

Grading:
    Course grades will be determined by the following weights: i) one comprehensive final exam -
covering all the material in the course: 50%; ii) quizzes given Tuesdays 3-3:50 in 9-283: 30%;
iii) Empirical paper and presentation in class (this may be completed in groups): 20%. The lowest quiz
score will be dropped. Students are encouraged to work together outside of class, but must be able to
individually demonstrate their understanding of the material on quizzes and the final exam. Regular class
attendance is essential to understand the material. In addition, attendance may directly affect grades in
borderline cases. No late “makeup” quizzes will be given.

The empirical paper and presentation may be completed individually or in groups of 2 or 3 students. It
should be brief (ideally less than 10 written pages, and less than 5 pages of charts, graphs, and other
ancillary material). It must be clearly written and substantive. You will likely want to prepare
PowerPoint slides for your presentation.
            OUTLINE – Tentative – Subject to Revision:

Date                 Topic                                                            Text Material

Sept. 25    Introduction:                                                             Ch. 1, 2.1

Sept. 30    Data and regression; models and notation
Oct. 2      Review statistical background for econometrics                            Sec. 2.2-2.3

Oct. 7      Regression using Excel
Oct. 9      Ordinary Least Squares, multivariate regression, R2                       Sec. 2.4, 2.5 Ch 3

Oct. 14     Restaurant Location Example
Oct. 16     Classical regression model; statistics review                             Ch. 4, (Ch. 16)

Oct. 21     Examples of real world data: OECD Health Data, internet data
Oct. 23     Hypothesis Testing, t-test and F-test                                     Ch. 5

Oct. 28     Introduce EViews software (available in lab)
Oct. 30     Specification - choice of independent (X) variables; Functional form      Ch. 6, 7

Nov. 4      Introduce SPSS software (available in lab and elsewhere on campus)
Nov. 6      Specification, , Multicollinearity; Serial Correlation                    Ch. 8, 9

Nov. 11     Veteran’s Day Holiday – no class
Nov. 13     Heteroskedasticity, Home price example from Ch 11                         Ch. 10, 11

Nov. 18     Work on Paper; Examples/Problems - Paper proposal due (1-2 pages)
Nov. 20     Wage differentials; Introduction to Time Series Data              Ch. 12

Nov. 25     Examples/Problems - Work on Paper/Presentation
Nov. 27     Thanksgiving, Holiday – no class

Dec. 1      Student Presentations
Dec. 3      Review and problem solving - Final Draft of paper due

Dec. 11 - Thursday           Final Exam - covering all course material (11:30-1:30 in 7-203)

NOTE:
- Quizzes will be given on Tuesdays 3-3:50 in 9-283
- Office hours are: Mon 1:30-4:30, Tu 12-1, and Th 12-1.
- Keep in contact with other students in class. Exchange phone numbers and/or emails with at least one
of your classmates. Be sure to find out what happened in any class you may miss. Studying in groups is
highly encouraged.
- There may be revisions to this syllabus. If so they will be announced in lecture.