Department of Economics Carnegie Mellon University

Econometrics II, 73-360 Fall, 2000-2001

Syllabus

Lectures  MW 10:30-11:20, PH A18A
Recitation A: F 10:30-11:20, OSC 201

B: F 10:30-11:20, PH A18B C: F 10:30-11:20, PH A18A

Instructor  Bill Vogt

HBH 2116D, 268-1843 wilibear@andrew.cmu.edu

Office Hours M 3:30 - 5:30

W 11:30- 2:00

TAs  A: Joshua Kimball, jkimball@andrew.cmu.edu

B: Amanda Pyles, apyles@andrew.cmu.edu C:

Textbooks Gujarati, Damodar (1992) Essentials of Econometrics.

New York, NY: McGraw-Hill. Delwiche, Lora D. & Susan J. Slaughter (1995) The Little SAS Book: A Primer. Cary, NC: The SAS Institute.

Website  http://www.andrew.cmu.edu/course/73-360/index.htm

1 Course Objectives

Our objective will be to build understanding of estimation and inference in several popular econometric models. These will include (time permitting) the multivariate linear regression model, models of discrete and limited dependent variables, and simultaneous equations models.

2 Prerequisites

The first course in this two course series is Econometrics I, 73-260. That course (or equivalent) is a prerequisite. Students are expected to understand basic probability, sampling, hypothesis testing, confidence intervals, and the bivariate linear regression model.

3 Grading

The grade will be determined by performance on homework assignments (30%), a midterm (30%), and the final exam (40%). You are responsible for the content of the lectures, including any handouts. The lectures cover material very similar to that presented in chapters 5-13 of the book. However, lectures do NOT follow the book exactly and it is the lecture material for which you are responsible.

4 SAS

For our class examples, homework, and tests, we will use the statistical package SAS. One of the texts for the course is a SAS primer. SAS is a general purpose statistical programming language. It is installed in more than 3 million sites world-wide and is nearly a de facto standard in the manipulation of large datasets. There will be instructional material on the website for SAS as well as several SAS review sessions in the evenings in a computer cluster.

5 Various Class Policies

1. Policy on Cooperation

• You may cooperate as much as you like on homework assignments; however, each individual must submit a separate assignment, and each individual will be separately graded on that assignment.

• You may not cooperate while taking exams.

2. Policy on Aids During Exams

• All exams are open book. You may use text, notes, calculators, computers, reference materials, etc.

• You may not communicate or cooperate with anyone on the exam.

• Please do not use the open book policy as a substitute for studying. If you need to look in your book, notes, etc for instructions on HOW TO DO the exam, you will surely run out of time.

3. Policy on Format of Assigned Work

• All work must be legible. Illegible is the equivalent of completely wrong.

• Spelling, grammar, style, etc do not “count” per se. However, anything which I (or the TAs) cannot understand is wrong. Poor spelling, grammar, style, etc are often confusing.

4. Policy on Lateness

• Due and return dates for assignments are in the syllabus in the schedule section. Unless the instructor or TA announces otherwise, these dates are binding.

• Late assignments are not accepted without either prior arrangement or compelling and verifiable reason.

• Assignments and homeworks will be returned to you in recitation. You are responsible for picking them up. You are responsible for keeping them to compare against your final grade. I will use whatever grade I have recorded for your work (even if you think there is an error) unless you can show me the graded work so that I can see the error.

• You are responsible for collecting your graded work. Claims by students similar to “I turned in homework #2, but I don’t have a copy of it because you did not return it to me!” must be made within one week of the return date of the assignment. If you fail to make the complaint in time, I will use whatever grade I have in my records.

6 Schedule

The class schedule below is tentative and likely will not be followed exactly. I offer it to give you an idea of which topics we will cover in what order and to give you an idea of how many assignments to expect.

Date  Material, Book Sections  Work
M Aug 28 Introduction

The Multivariate Model

W Aug 30 Assumptions of Model, 7.1, 7.2  HWK 1 assigned
F Sep 01 No Recitation
M Sep 04 No classes, Labor Day
W Sep 06 Estimation, Gauss-Markov, 7.3 6.3
F Sep 08 Recitation
M Sep 11 Confidence Intervals, Hypothesis Testing, 7.7
W Sep 13 Hypothesis Testing, several parameters, 7.8
F Sep 15 Recitation  HWK 1 due
M Sep 18 Examples  HWK 2 assigned

Functional Forms

W Sep 20 elasticity, log-log regression, 8.1-2
F Sep 22 Recitation
M Sep 25 growth, semi-log regression, 8.1-2
W Sep 27 dummy variables, 9.1-2
F Sep 29 Recitation  HWK 2 due
M Oct 02 dummies, many categories, 9.3-4  HWK 3 assigned
W Oct 04 Examples

Heteroskedasticity

F Oct 06 Recitation  HWK 3 due
M Oct 09 Consequences, 11.1-2
W Oct 11 Testing, Correcting, 11.3-4
F Oct 13 Recitation  HWK 3 returned

Date  Material, Book Sections  Work
M Oct 16 Examples/Review
W Oct 18 Midterm, covers through hetero
F Oct 20 No Recitation, Midsemester Break
M Oct 23 No Class, Midsemester Break

Serial Correlation

W Oct 25 Consequences, 12.1-2
F Oct 27 Recitation  Midterm returned

Specification Errors

M Oct 30 Omitted and Extraneous Variables, 13.1-2 HWK 4 assigned
W Nov 01 Multicollinearity, 10
F Nov 03 Recitation

Discrete Dependent Variables

M Nov 06 Discrete Dependent Variables Models  HWK 5 assigned
W Nov 08 Discrete Dependent Variables Models
F Nov 10 Recitation  HWK 4 due
M Nov 13 Idea of Maximum Likelihood
W Nov 15 Maximum Likelihood, Estimation, Inference
F Nov 17 Recitation  HWK 5 due, HWK 4 ret
M Nov 20 DDV examples  HWK 6 assigned
W Nov 22 No Class, Thanksgiving Break
F Nov 24 No Recitation
M Nov 27 Multinomial Logit

Limited Dependent Variables

W Nov 29 Limited Dependent Variables Models
F Dec 01 Recitation  HWK 6 due, HWK 5 ret
M Dec 04 Tobit Model
W Dec 06 Tobit Model, Estimation, Inference
F Dec 08 Recitation  HWK 6 returned
M Dec 11 Catch up & Review
Dec 14-9 Final Exams

Date Material, Book Sections Work