| |
Dec 14, 2025
|
|
|
|
|
ECON 5870 - Econometrics
This course provides students with a background in econometric theory. The main focus is on theory, but it also covers economic applications of econometric theory using data. Topics covered include the statistical foundations of the linear regression model, the least squares and maximum likelihood estimators as well as the methods to detect and correct potential problems with the classical regression model such as multicollinearity, heteroskedasticity, autocorrelation, and endogeneity. Models with binary regressors and models with qualitative dependent variables are introduced. Panel data models are also reviewed. Some computer assignments provide experience in empirical social science research.
Requisites: ECON 5000 concurrent
Credit Hours: 4
Repeat/Retake Information: May not be retaken.
Lecture/Lab Hours: 3.0 lecture
Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I
Learning Outcomes:
- Students will be able to explain the statistical properties of the OLS estimators in the context of the linear regression models and their assumptions.
- Students will be able to make standard and more advanced proofs related to the statistical properties of the OLS estimators in the context of the linear regression models.
- Students will be able to formally evaluate the failure of the assumptions to identify causality.
- Students will be able to perform econometric analysis using software and data with different structures.
- Students will be able to use Monte Carlo simulations in their econometric analyses.
- Students will be able to apply the fundamental concepts of linear regression analysis in more advanced courses in their future studies.
Add to Portfolio (opens a new window)
|
|
