Course Overview and Syllabus
Course info
| Day | Time | Location | |
|---|---|---|---|
| Lectures | Mon & Wed | 10:15 am - 11:30 am | Ruttan Hall B30 |
| Discussions | F | 1:55 pm - 2:45 pm | Ruttan Hall 135B |
Course Description:
This course is a continuation of Apec 8211 and 8212. It will cover maximum likelihood estimation, generalized method of moments estimation, multinominal and ordered logits and probits, censoring and selection models,density estimation, semi-parametric estimation, timeseries econometrics, dynamic panel data models, and machine learning. The focus will be on empirical work rather than on theoretical topics. Students should have completed Apec 8212 or an equivalent course.
Textbooks
The course will make use of the same textbooks used in Apec 8211 and 8212:
Both were published in 2022 by Princeton University Press. They are available both in hard cover and as e-books.
Grading
There will be homework and a final exam. Their weight in the final grade will be:
- Homework: 50%
- Final: 50% (Monday March 16, 10:15 a.m.)
Assignments:
Much of the homework will involve econometric estimation. You can do it using either R or Stata.
University Policies
The University of Minnesota requires that syllabi include references to the policies on student conduct; use of personal electronic devices in the classroom; scholastic dishonesty; makeup work for legitimate absences; appropriate student use of class notes and course materials; grading and transcripts; sexual harassment; equity, diversity, equal opportunity and affirmative action; disability accommodations; mental health and stress management; and academic freedom and responsibility. Please review them here: University Policy Library.