This course is designed to provide a foundation of econometric analysis, with an emphasis on economic applications.
This course is designed to provide a foundation of econometric
analysis, with an emphasis on
economic applications. Topics include estimation and statistical inference in regression models.
We begin with the standard regression model, and derive the properties of the estimators–
validity and efficiency. We will then relax assumptions one by one and explore how these
properties can be restored.
The ultimate goal is actual applications of econometric methods using the real data and
economic models, and therefore this course requires understanding of econometric software and
computing skills. For the empirical work, econometric computer software will be studied. The
recommended statistical software is Eviews. The teaching assistant (TA) will guide and assistyou to this computer software.
Class assignments will be passed out every three weeks approximately. These assignments will
include both problem solving and empirical tasks. The assignments will be graded by the
teaching assistant, and will be reviewed in the class. Class attendance and participation will becounted in the grade.
Team project will be given for each group of five students. The goal
of the project is to obtain
empirical assessment of economic models or any interesting subjects such as the consumption
function, Okun’s law, Taylor rule, MLB players’ salary determination, and forecasting the
gasoline price. Evaluation will be based on presentation and the term paper.
Jeffrey Wooldridge, Introductory Econometrics, 4th ed., Thomson South-Western
Paul Newbold, Statistics for Business and Economics, 6th ed.,
Berndt, Practice of Econometrics, Addison-Wesley.
Assignments: 20%. Midterm Exam: 30%. Final Exam: 30%.
Term Paper: 10%. Attendance: 10%.