Johan A. Elkink
teaching

Advanced Quantitative Methods

POL 50050 PhD Quantitative Methods II

Tuesday, 11 am-1 pm, on Zoom.

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.

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

1 19/1 Mathematics review & statistical estimators slides lab Notes: math review | statistical estimators
Videos: matrices | sampling distribution
2 26/1 Ordinary Least Squares slides lab Notes: regression tables
3 2/2 Regression diagnostics slides lab homework
4 9/2 Time-series analysis slides lab
5 16/2 Panel & multilevel data slides lab
6 23/2 Model specification & matching slides lab Notes: causal inference homework
7 2/3 Intrumental variables & regression discontinuity slides lab
8 23/3 Maximum Likelihood slides lab
9 30/3 Limited dependent variables I slides lab homework
10 6/4 Limited dependent variables II slides lab
11 13/4 Bootstrap & simulation slides lab Notes: bootstrap & simulation
12 20/4 Spatial & network data slides lab homework