Week 5: Maximum Likelihood Estimation and Heteroskedastic Regression
Schedule of the Week
Date |
Time |
Item |
Place |
Material |
|---|---|---|---|---|
| Mon, Mar 14 | 16:00–17:30 | Office hours (Oliver) | Zoom | |
| Tue, Mar 15 | 13:30–14:30 | Office hours (Thomas) | Zoom | |
| 15:30–17:00 | Office hours (Viktoriia) | Zoom | ||
| Wed, Mar 16 | 8:30–10:00 | Lecture | A5,6 B244 | |
| 10:00 | Homework 3 is assigned | Github | ||
| Thu, Mar 17 | 10:15–11:45 | Lab (Oliver) | A5,6 B317 | |
| 15:30–17:00 | Lab (Viktoriia) | Zoom |
Study Notes
Make sure you closely (re)-read the entire King’s UPM, chapter 4. For those of you who appreciate a slightly different take on MLE take a look at Eliason (1993). Please also read a short section in Long (1997) chapter 3.6.1 and 3.6.2 in order to get a sense of how to actually estimate standard errors using maximum likelihood. For an nice application on how to set-up a heteroskedastic regression model take a look at the “classic” Franklin (1991) paper (this paper will also be relevant for your third homework!). Alternatively, another interesting application of a heteroskedastic regression model is found in Golder and Lloyd (2014).