Day(s)
Tu
-
Th
Time(s)
1:30 PM - 2:50 PM
Course ID
42000
Term
Winter 2018

This course is the first in a two-part sequence designed to cover applied econometrics and regression methods at a fairly advanced level. This course provides a theoretical analysis of linear regression models for applied researchers. It considers analytical issues caused by violations of the Gauss-Markov assumptions, including linearity (functional form), heteroscedasticity, and panel data. Alternative estimators are examined to deal with each. Prerequisites: This course is intended for first or second-year Ph.D. students or advanced masters-level students who have taken the Statistics 24400/24500 sequence. Familiarity with matrix algebra is necessary.

Notes

PhD and MACRM only. Other masters students by consent only.