R is an open-source statistical programming language. It is available from the following website: R-Cran. You should install R on you laptop. For us it is probably best to use the following link. You can also install R-Studio which is an Integrated Development Environment (IDE) for R.
R is one of the main programmable statistical languages. Others include: - Stata: Used in academic econometrics. This is not open source. - Matlab: Used extensively in academic finance. It is not open-source. There is an open-source clone called Octave. It can be downloaded here. - Python: Computer Language for statistical programming.
- Julia: New language that is faster than R - C++: Programming language. Underneath R is C++ in some cases.
The main advantages of using an open-source statistical programming language like R are: - It can be used by anyone for no cost. Your model will not depend on the next institution having the same software licence - You can read and adjust functions that have been created by other people - There is a large community of people to help you - Your model will not depend on the next institution having the same software licence (do firms use Eviews?) - Programming language will encourage reproducible research
Reproducible Research is good practice and it means that results can be easily replicated. This means - Mistakes can be more swiftly identified - Changes to data or research methods are easier to make - Replication and clarity are increasingly important for compliance in financial institutions
Some additional information on R, R-Studio and Reproducible Research - European repository on spreadsheet horror stories - LSE commentary on reproducible research with a section on Reinhart and Rogoff - Quick R - R Course on DataCamp