Statistics for Experimental Economists SS 2007

This course is part of the International Max Planck Research School on Adapting Behavior in a Fundamentally Uncertain World. The target group are students who, due to the interdisciplinary nature of the IMPRS school, do not have any background in statistics

Termin:

Lecture (daily): 13.8.-17.8., 8:15-9:45, 14:15-14:45

Topics:

• Introduction
• Elementary Probability Calculus
• Random Variables
• Stochastic Models and Distributions
• Limit Theorems
• Point Estimation
• Estimation of Intervals
• Basic Statistical Tests
• OLS Regression
• Maximum Likelihood (if time permits)
• Choice Models (if time permits)
• Censored Models (if time permits)

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 and R has the advantage of being free and rather powerful.

• Documentation for R is provided via the built in help system but also through the R Homepage. Useful are
  • The R Guide, Jason Owen (Easy to read, tries to explain R with the help of examples from basic statistics)
  • Simple R, John Verzani (Tries to explain R with the help of examples from basic statistics)
  • Einführung in R, Günther Sawitzki (In German. Rather compact introduction. The statistical part can be quite demanding)
  • Econometrics in R, Grant V. Farnsworth (The introduction to R is rather compact and pragmatic. The econometric models go beyond what we are doing in this lecture)
  • 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. A must to read if you write your own functions)
• A first entry into R eased through mice and menues is available through the R Commander.
• An interesting development environment is RStudio.
• In the lecture I use the versatile editor Emacs with the ESS interface (ESS also helps with Stata, SAS, Splus, BUGS, and others). Users of MacOS-X will prefer the Emacs-Clone aquamacs.

Handout + Exam

The handout will be updated a few times. Data is also attached to the handout. If you wish you can have a look at the exam. I have added some notes that might help you in finding a solution.

Literature

• Stock and Watson; Introduction to Econometrics; 2nd Edition; Pearson 2006.
• Michael Murray; Econometrics, a Modern Introduction; Pearson 2006
• William Greene, Econometric Analysis, Prentice Hall, 6th Edition, 2003.
• Christian Gourieroux and Alain Monfort, Statistics and Econometric Models, Vol. 1, Cambridge, 1995.