University of California
Department of Economics
Doug Steigerwald
Introduction to Econometrics
Economics 140A
Course Prerequisites:
Students should be familiar with calculus (Mathematics 3A-3C), the fundamentals of
statistical inference (Statistics 120A) and economics (Economics 100A-B and 101). In addition,
Statistics 120B is recommended.
Course Requirements:
Students will be graded on ten problem sets, a class project and final examination. The
problem sets must be turned in before class on the date due, without exception. The ten problem
sets contribute 20 percent toward the final grade, while the project and final examination each
contribute 40 percent.
Course Textbooks:
Required:
A. Studenmund, Using Econometrics: A Practical Guide, Addison-Wesley, 2001.
P. Kennedy, A Guide to Econometrics, MIT 2003.
Recommended:
T. Amemiya, Introduction to Statistics and Econometrics, Harvard University, 1994.
O. Ashenfelter, Statistics and Econometrics: Methods and Applications, Wiley, 2003.
J. Farlow, Differential Equations and Linear Algebra, Pearson-Prentice Hall, 2001.
R. Larsen, Introduction to Mathematical Statistics, Pearson-Prentice Hall, 2000.
G. Maddala, Introduction to Econometrics, Wiley, 2001.
J. Stock and M. Watson, Introduction to Econometrics, Addison-Wesley, 2003.
J. Wooldridge, Introductory Econometrics, South-Western, 2001.
References:
Each of the required and recommended texts has been placed on library reserve.
Course Schedule
Monday, September 26:
Statistical Review: Random Variables
Amemiya 1, 2.1-2.2, 3.1, 4; Studenmund 16.1-16.2
Wednesday:
Problem Set I due
Statistical Review: Properties of Estimators
Amemiya 7.1-7.2; Studenmnund 16.3-16.4
Monday:
Statistical Review: Confidence Intervals and Hypothesis Testing
Amemiya 8.1-8.2, 9.1-9.6; Studenmund 16.5-16.6
Wednesday:
Problem Set II due
Linear Regression: Population Regression Models
Maddala 3.0-3.2, 3.11-3.12; Studenmund 1, 4.1-4.2
Economics 140A
Syllabus
Monday:
Linear Regression: Regression Model Estimators
Maddala 3.4, 3.8; Studenmund 2, 3
Wednesday:
Problem Set III due
Linear Regression: Properties of OLS Estimators
Maddala 3.5; Studenmund 4.3
Monday:
Linear Regression: Optimality of OLS Estimators
Amemiya 7.3-7.4; Maddala 3.3; Studenmund 4.4-4.6
Wednesday:
Problem Set IV due
Linear Regression: Hypothesis Testing in Regression Models
Maddala 3.7, 4.0-4.8; Studenmund 5
Monday:
Regression Problems: Regressor Specification
Maddala 4.9-4.11; Studenmund 6
Wednesday:
Problem Set V due
Regression Problems: Functional Form Specification
Maddala 3.9; Studenmund 7
Monday:
Regression Problems: Measurement Error and Multicollinearity
Maddala 7; Studenmund 8, 14.6
Wednesday:
Problem Set VI due
Regression Problems: Estimation with Instruments
Studenmund 11
Monday:
Regression Problems: Error: Location and Scale Variation
Maddala 5; Studenmund 10
Wednesday:
Problem Set VII due
Regression Problems: Error: Serial Correlation
Maddala 6.0-6.9; Studenmund 9
Monday:
Regression Problems: Error: Non-Gaussian Distribution
Maddala 10.17
Wednesday:
Problem Set VIII due
Regression Extensions: Qualitative Dependent Variables
Studenmund 13
Saturday-Sunday, November 19-20
Class Project Presentation
Monday November 21:
Thanksgiving Holiday
Wednesday November 23:
Thanksgiving Holiday
Monday:
Simultaneous Equation Models: Identification
Studenmund 14.1,14.4-14.5
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Economics 140A
Syllabus
Wednesday:
Problem Set IX due
Simultaneous Equation Models: Two-Stage Least Squares Estimation
Studenmund 14.2-14.3
Final Examination: Thursday, December 8
8:00 – 11:00 am
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