Econometrics with R

“R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS.”

The R Project for Statistical Computing

R is considered an implementation of the S language

• A Brief History of S
  by Richard A. Becker, AT&T laboratories

A brief history of me and R

I have learnt to use R for statistical computing and graph since January 2011. I came across R as I was looking for a software that can run SEM (Structural Equation Model) for my PhD research in my MacBook. At the time (2010), there was no other softwares that allow me to run SEM directly in a Mac. The only way is to use Bootcamp to operate the Window system in MacBook and run SEM software for PC e.g., Lisrel, AMOS or Mplus. Then I googled “Structural Equation Modelling in Mac” and found the ‘sem‘ package by John Fox  in software called ‘R’. I also found that there were two developing packages that would be able to run SEM in R. They are OpenMx and lavaan. I did not used R immediately since it seemed to me that R requires some programming skills which I had none at the time. However, when I managed to give it a go. I found that R is really powerful. It is not only free as in beer but also as freedom. R is an open-source statistical software, probably the most popular one. Anyone can create a package to run in R. Such software could be just a database, basic or advance statistical methods. Moreover, it can be run in both PC and Mac with high compatibility. Since then I have been a big fan of R. Even though now I am just an R useR but I believe that I will be an R contributoR soon.

New: I just launched a Twitter account on Econometrics Applications of R. You can follow us @R4Econ

Blog post about R (see all)

• R Tutorials from Universities Around the World

Manuals

1. Econometrics with R (English)
2. Statistics with R (in Thai)

My contributed packages

1. econ (work in progress)
   This package aims to provide statistics and econometrics analysis, graphics especially for supply chain applications.
2. scm (work in progress)
   This package aims to provide data sets of supply chain management analysis.
3. tour (work in progress)
   This package aims to provide data sets of tourism  analysis.

External links on ‘Econometrics with R’

1. CRAN Task View: Computational Econometrics
   by Achim Zeileis
2. Reviews on books and other resources on Econometrics with R
   by Rob J Hyndman 
3. Econometrics in R (CRAN)
   by Grant V. Farnsworth
4. A Brief Guide to R for Beginners in Econometrics (PDF)
   by Mahmood Arai
5. Panel Data Econometrics in R: The plm Package (JSS)
   by Yves Croissant and Giovanni Millo
6. Applied Econometrics with R (Use R!) [Paperback] (Amazon)
   by Christian Kleiber and  Achim Zeileis
7. Resources about R software
   by The Econometrics Journal Online
8. R for Econometricians
   by David Smith (Revolution Analytics)

Econometrics manuals using R

1. Forecasting: principles and practice
   An online textbook by Rob J Hyndman and George Athanasopoulos
    

Special issue 1: Extreme value

1. Econometry of Financial Market with R-project
   by Daniel Herlemont
2. Several packages provide functionality for Extreme Value Theory models: evd, evdbayes, evir, extRemes, ismev, POT.
   (From CRAN taskview on Finance)
3. R Packages and Bundles necessary to develop Stress Testing and Economic Capital Estimation (PDF)
   by John A. Morrison