## Advanced Quantitative Methods

POL 50050 **PhD Quantitative Methods II**

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

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 |
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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 |