Here you can find all the material you need for the class - the lecture slides, links to lab repos on Github, readings for the week.
|
|
| Week 1 |
Introduction. OLS Recap |
|
|
|
|
| Week 2 |
OLS in Matrix Form |
|
|
|
|
| Week 3 |
OLS in Matrix Form and Probability Theory |
|
|
|
|
|
|
| Week 4 |
A first peek at Maximum Likelihood |
|
|
|
|
| Week 5 |
Maximum Likelihood Estimation and Heteroskedastic Regression |
|
|
|
|
| Week 6 |
Models for Binary Dependent Variables & Model Fit |
|
|
|
|
| Week 7 |
Interpretation and Simulation |
|
|
|
|
| Week 8 |
Ordered Choice Models & How to write a publishable Paper |
|
|
|
|
| Week 9 |
Multinomial Choice Models |
|
|
|
|
| Week 10 |
Conditional Logit Model |
|
|
|
|
| Week 11 |
Selection Bias and Multi-Equation Models |
|
|
|
|
|
|
| Week 12 |
Multi-level Models |
|
|
|
|
| Week 13 |
Baby Bayes – a primer |
|
|
|
|
| Week 14 |
Student Presentations |
|
|
|
|