Lecture Econometrics IIb SS 2012

This lecture is (in SS 2012) equivalent to MW24.5 - Quantitative Economics II from the Master Program.

Lecture:

6.-10.8.2012, MPI Economics, Room V14

Audience

The lecture is primarily targeted at graduate students. Advanced students from the Hauptstudium are welcome.

Requirements:

A basic knowledge of statistical or econometric methods is helpful. In the course we will mainly put methods to use and not discuss why and when certain methods are appropriate.

Handout

Exam

Topics

• Introduction
• User interfaces for R
• Syntax
• Representing data
• Reading data
• Control structures
• Functions
• Input and output of data
• Graphs
• Simple Regressions
• ...

Software

For our practical examples (during the entire course) we will use the software environment R. I think that it is helpful to coordinate on one environment. R is free, it is very powerful, and it is popular in the field.

• Documentation for R is provided throught the built in help. You also find support on the R Homepage. You might find the following useful:
  • The R Guide, Jason Owen (Easy to read, explains R with the help of examples from basic statistics)
  • Simple R, John Verzani (Explains R with the help of examples from basic statistics)
  • Einführung in R, Günther Sawitzki (In German. Rather compact introduction.)
  • Econometrics in R, Grant V. Farnsworth (The introduction to R is rather compact and pragmatic.)
  • An Introduction to R, W. N. Venables und D. M. Smith (The focus is more on R as a programming language)
  • The R language definition (Concentrates only on R as a programming language.)
• You can download R from the homepage of the R-project.

  Installing R with Microsoft Windows:

  Download and start the Installer. Install R on your local drive. Installing on a network drive or in the cloud (Dropbox, Onedrive,...) is possible but not recommended.

  Installing R with GNU-Linux:

  Follow the advice to install R for your distribution.

  Installing R with MacOS X:

  Here is a guide to install R with MacOS X.

• In the lecture we use RStudio as a front end.
• We will use the following packages: car, Ecdat, MASS (VR), UsingR, binom, relaimpo, lmtest, mvtnorm, lattice, clinfun, memisc, xtable.

  If, e.g., the command library(Ecdat) generates an error message (Error in library(Ecdat): There is no package called 'Ecdat'), you have to install the package.

  Installing packages with Microsoft Windows:

  With RStudio: Use the tab “Install”. Otherwise: Start Rgui.exe and install packages from the menu Packages / Install Packages).

  Installing packages from GNU-Linux or MacOS X:

  From within R use the command install.packages("Ecdat"), e.g., to install the package Ecdat