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Free Software

The following is a list of free open-source software. We do not teach the use of these programs in our courses. We teach using software that you may encounter is the workplace. Support for these packages is limited, though there are large user-communities for each progam.

Follow these links to free Statistical packages. The Econometrics Journal has compiled a list of econometric software, both commercial and freeware.


FreeMat is a free environment for rapid engineering and scientific prototyping and data processing. It is similar to commercial systems such as MATLAB from Mathworks, and IDL from Research Systems, but is Open Source. FreeMat is available under the GPL license.

gretl: Gnu Regression, Econometrics and Time-series Library

gretl is a cross-platform software package for econometric analysis, written in the C programming language. It is is free, open-source software.


JMulTi was originally designed as a tool for certain econometric procedures in time series analysis that are especially difficult to use and that are not available in other packages, like Impulse Response Analysis with bootstrapped confidence intervals for VAR/VEC modelling. Now many other features have been integrated as well to make it possible to convey a comprehensive analysis. Limitations of this software can be overcome by exporting datasets or computation results and use them with other programs.


GNU Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command line interface for solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with Matlab. It may also be used as a batch-oriented language.


R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.


Scilab is the free software for numerical computation providing a powerful computing environment for engineering and scientific applications.