Download ECON 7818-001 Econometrics I

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Economics 7818
,
Dr. Waldman, Econ. 222, tel. 492-6781
Office hours: To be determined
January 16, 1996
email: [email protected]
Course Information
General: Economics 7818 is a one-semester course in statistics for economics Ph.D.
students. It is the first course in the two-semester requirement in statistics/econometrics. The fundamental tool of applied economists ( and other social scientists) is
regression analysis. The purpose of this course is to present the mathematical statistics
foundation for the study of regression analysis. Regression analysis is the topic of
Economics 7828.
Prerequisites: There are no economics course prerequisites. Economic examples will be
used in class and for problem sets, but the subject matter is essentially self-contained.
General prerequisites are a knowledge of differential and integral calculus, and more
importantly, the ability to think mathematically.
Requirements: There will be two lectures weekly, meeting Tuesdays and Thursdays
from 9:30 to 10:45. There will be a quiz (given in about three weeks), a midterm exam,
Thursday, :i\,1 arch 7, a final exam, and periodic problem sets given throughout the
semester.
Grading: Grades will be determined approximately as follows:
Quiz:
Midterm:
Final exam:
Residual:*
5%
30%
40%
25%
*This includes problem sets, class participation, contact m office hours, subjective
scoring of written work, etc.
Text: Introduction to Statistics and Econometrics, by Takeshi Amemiya, Harvard University Press, 1994.
Tentative course outline: The first nine chapters of the text will be covered, in the order
presented:
Week
Chapter
1
1
2
3, 4
5, 6
2
3
4
5
7
8
9, 10
11
12
13
14
15, 16
6
7
7
8
9
Topics
Introduction and basic probability concepts
Basic probability concepts, continued
Random variables and probability distributions
Moments of a distribution
Binomial and normal random variables
Midterm review and midterm
Large sample (asymptotic) theory
Point estimation
Spring break
Point estimation (continued)
Interval estimation and Bayesian methods
Hypothesis testing, review