This class was tough.
Course Overview:
This course focuses on techniques for estimating regression models, on problems commonly encountered in estimating such models, and on interpreting the estimates from such models. The goal of the course is to teach you the basics of the theory and practice of econometrics and to give you experience in estimating econometric models with actual data.
Course highlights:
Simple linear regression: WR, Chapter 2 9/12 Simple linear regression: WR, Chapter 2 9/17 Simple linear regression: WR, Chapter 2 9/19 Quiz #1; no lecture 9/24 Multiple linear regression – estimation; WR, Chapter 3 9/26 Multiple linear regression – estimation; WR, Chapter 3 10/1 Multiple linear regression - estimation: WR, Chapter 3 10/3 Quiz #2; Multiple linear regression – estimation: WR, Chapter 3 10/8 Multiple linear regression – inference: WR, Chapter 4 10/10 Multiple linear regression – inference: WR, Chapter 4 10/15 No meeting – fall break 10/17 Multiple linear regression – inference: WR, Chapter 4 10/22 Multiple linear regression – inference: WR, Chapter 4 10/24 Midterm exam 10/29 Multiple regression – OLS asymptotics: WR, Chapter 5 10/31 Multiple regression – further issues: WR, Chapter 6 11/5 Quiz #3, Multiple regression – further issues: WR, Chapter 6 11/7 Multiple regression – qualitative variables: WR, Chapter 7 11/12 Multiple regression – qualitative variables: WR, Chapter 7 11/14 Heteroskedasticity: WR, Chapter 8 11/19 Quiz #4, Heteroskedasticity: WR, Chapter 8 11/21 Bonus lecture on social experiments
Hours per week:
9-11 hours
Advice for students:
This is a challenging course. If you do not want to be challenged, you should take a different course. This course is one that you should take if you plan to go on to graduate school in economics, criminology, education, political science, public policy or sociology.