Vorlesung Ökonometrische Verfahren (Winter 2012/13)Diplom students can take MW24.1 - Empirical Methods as equivalent to this lecture. At the end of the lecture an exam in "Ökonometrische Verfahren" can be written.
- Nadine Chlaß
- As a block:
- Mo, 12.11.2012, SR 308,
- Other material
- Basic mathematical and statistical methods as provided, e.g., in BW24.1
- The classical OLS model
- Irrelevant and omitted variables
- Model selection
- Nonlinear models
- Using Maximum Likelihood
- Identification strategies
- Stock and Watson; Introduction to Econometrics; 2nd Edition; Pearson 2006.
- alternatively: Stock and Watson; Introduction to Econometrics; Brief Edition; Pearson 2008
- Michael Murray; Econometrics, a Modern Introduction; Pearson 2006
- Studenmund; Using Econometrics; 5th edition; Pearson 2006.
- Barreto and Howland; Introductory Econometrics; Cambridge 2006.
- Examples from the lecture
- In the lecture I will often use real applications as illustrations. I recommend that you try these applications on your own. To do this, open R and type the following:
data(Caschool,package="Ecdat")from now on all commands refer to this dataset:
large=factor(str>20)A brief documentation of the variables of this dataset can be obtained with
- 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
- 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.
- Mo, 12.11.2012, SR 308,