Johan A. Elkink
teaching

Advanced Quantitative Methods

POL 50050 PhD Quantitative Methods II

Friday, 1-4 pm, room G317, Newman Building (building 41 on the campus map).

Syllabus

While the statistical package R is the software used on slides, students can use any package of choice. A booklet with commands in R, Stata, and SPSS will be made available. R can be downloaded for free here. A handy overview of R regression commands can be found here: reference card for regression. A more general one for R is here: short reference card. Finally, there is an extensive overview of R packages relevant for econometrics.

A booklet is in production with all relevant commands for the course in a number of different statistical packages, with an early draft here: Statistical Software Guide for Introductory Econometrics. Since we are actively working on this booklet, any feedback would be greatly appreciated.

For R users, please make sure to install the following packages prior to the second lecture of the course:
faraway, arm, lmtest, tseries, ape, MASS, plm, and pcse.

It is generally advisable to bring electronic copies of slides and lecture notes (where applicable) to the class. I would recommend not to print the slides, however, since these are large files. There is also WiFi access available in-class.

Data can be found on the teaching data page, but for homeworks also original replication data sets might be used.

1 26/1 Mathematics review & statistical estimators slides lab notes | notes
2 2/2 Ordinary Least Squares slides lab notes
3 9/2 Regression diagnostics slides lab homework
4 16/2 Time-series analysis slides lab
5 23/2 Panel data slides lab homework
6 9/3 Cancelled due to weather conditions - merged with next lecture
7 6/4 Causal inference slides lab notes
8 10/4 Maximum Likelihood slides lab homework
9 13/4 Limited dependent variables slides lab
10 27/4 Bootstrap and simulation slides lab notes homework
11 4/5 Networks and spatial data slides lab