Farnsworth G.V. Econometrics in R

Grant V. Farnsworth, 2008. – 50 p. – ISBN: N/AR is much more more flexible than most software used by econometricians because it is a modern mathematical programming language, not just a program that does regressions and tests. This means our analysis need not be restricted to the functions included in the default package. There is an extensive and constantly expanding collection of libraries online for use in many disciplines. As researchers develop new algorithms and processes, the corresponding libraries get posted on the R website. In this sense R is always at the forefront of statistical knowledge. Because of the ease and flexibility of programming in R it is easy to extend.
The S language is the de facto standard for statistical science. Reading the statistical literature, we find that examples and even pseudo-code are written in R-compatible syntax. Since most users have a statistical background, the jargon used by R experts sometimes differs from what an econometrician (especially a beginning econometrician) may expect. A primary purpose of this document is to eliminate this language barrier and allow the econometrician to tap into the work of these innovative statisticians.
Code written for R can be run on many computational platforms with or without a graphical user interface, and R comes standard with some of the most flexible and powerful graphics routines available anywhere.
And of course, R is completely free for any use.Introductory Comments.
Working with Data.
Cross Sectional Regression.
Special Regressions.
Time Series Regression.
Plotting.
Statistics.
Math in R.
Programming.
Changing Configurations.
Saving Your Work.
Final Comments.
Appendix: Code Examples.