Course #
42000

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.

Course Sections

Quarter Instructor(s) Day(s) Time(s)
Winter 2018 Jeffrey Grogger Tu, Th 1:30 PM - 2:50 PM