ECON 321: Econometrics
Prerequisites: STAT 200; ECON 105, ECON 106; and one of the following: MATH 126 or
MATH 151, MATH 169, or MATH 171
Credit hours (3)
This course teaches students how to apply statistical methods to the analysis of economic
data in order to test economic theories and produce forecasts. It uses the least
squares regression theory to produce estimators and analyzes how to deal with problems
unique in the analysis of economic data, such as heteroskedasticity, autocorrelation,
and multicollinearity.
| Note(s): Scientific and Quantitative Reasoning designated course. Students cannot receive credit for both ECON 421 and ECON 321. |
Detailed Description of Course
Econometrics uses tools from statistics to test economic theory and reasoning. The main objective of the course is to provide students with hands-onexperience in the empirical elements of a basic economic study: (1) presenting data effectively in charts and tables; (2) identifying interesting economic trends and relationships in data; (3) constructing and testing hypotheses based on economic reasoning that explain what is observed; (4) identifying and correcting for problems unique in the analysis of economic data; and (5) identifying the limitations and shortcomings of an analysis. The course covers the empirical techniques used most frequently in research, policy-making and consultancy: least squares regression methods, time series modeling and the basics of forecasting. Students will use statistical software to perform assigned tasks and to complete analyses on topics of their own interest.
Detailed Description of Conduct of Course
The following teaching strategies may be employed:
Lecture, discussion, homework sets with heavy computer use. All students have to
write a paper using economic data and demonstrating their knowledge of econometric
concepts.
Goals and Objectives of the Course
Students at the end of the course will be able to:
1) Derive the least squares estimators in the simple regression model.
2) Do hypothesis testing using the specific values of the estimators.
3) Write and execute computer programs that detect and correct for (a) autocorrelation,
(b) heteroscedasticity, and (c) multicollinearity.
4) Read most of the results on a SAS computer printout including the ANOVA table
and the
R-squared statistic.
5) Use econometric models to make predictions.
Assessment Measures
May include: tests, homework assignments, essays, and exams.
Other Course Information
None
Review and Approval
September 2, 2014
December 2013 C. Vehorn
April 16, 2012
September 2001 N. Hashemzadeh, Chair
March 01, 2021