Quantitative Economics TT 2023

Format. We will meet in larger groups in odd weeks and smaller groups in even weeks. In week 7 we will have a large R-class with everyone instead of the large group meeting. The larger groups will run more like classes, whereas the smaller groups will run as tutorials. In tutorials, we will cover the problem set but also have time for extension material and discussion. In classes, we will stick closer to the problem sets and go over the solutions in detail. In even weeks I will also be running office hours which are entirely optional and open to everyone to drop in and out of, with additional questions they may have about that week's material but didn't have time to ask in the tutorial itself.

Hand in work. The recommended problems (and readings) corresponding to week t should be handed in on Tuesday at 9 am of week t+1 and will be covered in our meeting on Thursday of week t+1.  For each problem sheet only complete the reccomended problems indicated at the beginning of the sheet. The work for each meeting is explained below.  Hand work into my pidge at Corpus, do not email me an electronic copy of your work. The tutorials (in even weeks) may have small additional tasks or readings you're expected to complete before the tutorial.

Marking. Only work submitted for the small group tutorials in weeks 2, 4, and 6 will be marked. Work that is handed in late will not be marked. 

Scheduling. In even weeks the tutorials will be 1h long, in odd weeks the classes will be 2h long. I will additionally hold office hours from 10:00-10:30 and 17:30-18:30 in each even week. All classes and tutorials will be held on Thursdays. 

Tutorial discussion topics. In even weeks we will utilise the tutorial format to have a more engaged discussion. We will spend about 30mins covering tricky bits of the problem set, but as your work will be marked in these weeks there is no need to cover everything (and the office hours are there to answer any remaining questions you may have). We will then spend 30mins extending the material or bringing it to an application. You are expected to familiarise yourself with the material and topics below before the tutorial in order to engage in the discussion, you are also encouraged to read widely around the topic, do not feel constrained by what I suggest. 

Class 1 (week 1)

Course topic: Probability and Statistics

Hand in work: Worksheet 1

Tutorial 1  (week 2)

Course topic: Linear regression and causality

Hand in work: Worksheet 2

Applied Topic: Regression interpretation in the wild

Discussion material: HuffPost Article, Politico Article, Guardian Article

Class 2 (week 3)

Course topic: Linear regression and statistical inference

Hand in work: Worksheet 3

Tutorial 2  (week 4)

Course topic: Linear regression and statistical inference

Hand in work: Worksheet 4

Applied Topic: Machine learning

Discussion material: Primer on LASSO and Ridge regression, Questions for discussion

Class 3 (week 5)

Course topic: Endogeneity

Hand in work: Worksheet 5

Tutorial 3  (week 6)

Course topic: Endogeneity

Hand in work: Worksheet 6

Applied topic: Example from academic work

Discussion material: David Card (1990) Mariel Boatlift 

Class 4 (week 7) R Class

Course topic: R

Hand in work: R handouts 1, 2, and 3

Tutorial 4  (week 8) 

Course topic: Time series

Hand in work: Worksheet 7 (questions 2 and 4 only) and worksheet 8 (questions 2 and 4 only)

Applied topic: Panel data and event study designs applied to the 'child penalty'.

Discussion material: Panel data primer (sections 1,2,3,4), CEPR article, AER article, (optional: Kleven et al. (2019))