Johan A. Elkink
teaching

Advanced Quantitative Methods

POL 50050 PhD Quantitative Methods II

Thursday, 9-11 am, room G317, Newman Building (building 36 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.

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 slides lab notes
2 2/2 Statistical estimators slides notes
3 9/2 Ordinary Least Squares slides lab notes homework
4 16/2 Regression diagnostics slides lab
5 23/2 Time-series analysis slides lab homework
6 2/3 Causal inference slides lab notes
7 14/3 (!) Maximum Likelihood slides lab homework
8 30/3 Limited dependent variables I slides lab
9 6/4 Limited dependent variables II (continued) (continued)
10 13/4 Bootstrap and simulation slides lab notes homework
11 20/4 Multilevel and panel data slides lab
12 27/4 Spatial and network data slides lab | output