One possible solution is to use free software. Free software is software that can be used, studied and modified without restriction. It can be copied and redistributed free in the original or modified format provided that the recipients of the redistributed form also have these rights. In general full source code for the original or modified form must be made available. This allows one to build and extend the work of others without having to start from basics. In the field of statistics much empirical research into new methods is being done in R and it is likely that this R will be used more and more in econometrics. For example Chris Sims has switched to using an R version of his VarTools in his own research.

I have used free software for many years. It is often easier to use (e.g. gretl) and sometimes more up to date than commercial software. Sometimes it contains facilities that are not generally available in commercial software (e.g. jMulti). This note describes the main items of free software that I have used over the years. It is a personal list and covers only a small portion of such software. While the emphasis here is on software for Microsoft Windows versions are also available for Linux and for Apple Mac. You will find comprehensive lists of free and commercial software at http://www.feweb.vu.nl/econometriclinks/software.html and in the AEA Resources for Economists on the Internet. The software listed in the index below covers most of the applications that an econometrician or economist might require. The descriptions that follow are a mixture of my own comments and extracts taken from descriptions of the software taken from the web.

- Obtaining Gretl: Quoting from http://gretl.sourceforge.net/, gretl is a cross-platform software package for econometric analysis, written in the C programming language. It is free, open-source software. You may redistribute it and/or modify it under the terms of the GNU General Public License (GPL) as published by the Free Software Foundation. A windows version may be downloaded by selecting gretl for Windows on the list on the left hand side of the home page. There are two versions of the install program available gretl-1.9.5.exe and gretl_install.exe. The first of these is the latest “stable” version. The second is the latest development snapshot which may contain some updates and bug fixes but may have some new bugs. I use the second version and update occasionally. I keep the previous version in case I need to revert but this has not been necessary. A user’s guide and a reference manual are contained in the download or may be downloaded separately from the web-site.
- Installing gretl: Installation is simple. Double click on the downloaded file and follow the instructions. You may accept the suggested defaults.
- Other gretl resources:

- The gretl web site contains versions of the X12-ARIMA and TRAMO/SEATS seasonal adjustment programs that can be called from within gretl and can save their output in gretl format
- The web site also contains data sets and script files for

- Wooldridge, Introductory Econometrics

- Gujarati, Basic Econometrics

- Stock and Watson, Introduction to Econometrics

- Davidson and MacKinnon, Econometric Theory and Methods
- Marno Verbeek’s Guide to Modern Econometrics

- Lee Adkins gretl page, http://www.learneconometrics.com/gretl.html contains a down loadable guide to the use of gretl with (Using gretl for Principles of Econometrics, 3rd edition) and other useful links.
- There is a gretl wiki site at
http://gretlwiki.econ.univpm.it/wiki/index.php/Main_Page. This also
contains some useful links

- Using the programs graphical user interface (GUI) – This is similar to many other Windows programs where you use the mouse and mouse clicks to select various actions from drop-down menus. As you will see most of the menus are self explanatory. For the moment to start the GUI just double click on the gretl icon that the install program that the installed on your desktop.
- Using gretl scripts – All these menu items can be completed by issuing commands in the gretl programming (script) language. These commands can be saved to a file and the set of instructions in the file can be rerun from the saved file. (In some organizations the internal audit function (or management may insist that a record of econometric analysis be kept to aid replication. Unless the work is of a very simple nature this is the only way to ensure that an analysis can be replicated.)
- Combining GUI and scripting – If you run Gretl from the GUI it
has the facility to save the menu choices and options you take as a
script file. You may then use and possible expand and amend that script
file as a basis for further analysis.

In working through any econometric project I recommend that one set up a specific directory or subdirectory for that project (C:\Users\frainj\gretl\introduction). I can specify that directory as working directory using the|File|Working Directory| menu item as in the following Figure.

In that directory I have an Excel file denmark .xls which is illustrated in the figure below.

The data set is a rectangle with observations in rows and series in columns. Missing data can be represented by blank cells, by NA or several other options. (See users’ guide). The data are imported from Excel using the Menu items |File|Open Data|Import|Excel| and selecting the relevant file. Gretl will try to determine various features of the file and will ask you to confirm these features. (It generally does this well). In the current case it determines that the data are time series and labels the observations with the correct dates. The data are now entered on the Gretl Workplace. Gretl can import data from

a large number of other programs

- Plain text (ASCII) files – These can be brought in using gretl's |File|OpenData| Import ASCII. . . | menu item, or the import script command. For details on what gretl expects of such files, see Section 4.4. of the users’ guide.
- Comma-Separated Values (CSV) files – These can be imported using
gretl's |File|Open Data|Import CSV. . . menu item, or the import script
command. See also Section 4.4.

- Spreadsheets: MS Excel, Gnumeric and Open Document (ODS) – These are also brought in using gretl's |File|Open Data|Import| menu. The requirements for such files are given in Section 4.4. of the user’s manual
- Stata data files (.dta).
- SPSS data files (.sav).
- Eviews workfiles (.wf1)
- JMulTi data files

Gretl has its own native data format and it is possible to save all or a selection of our data in this format with the menu item |File|Save Data|. It can then be loaded directly from the |File| Open Data|User File| menu item.

Examining the menu items shows the variety of work that can be completed in gretl. The following graph and its annotations were produced in two steps.

- A basic graph containing the two series was produced using
the menu item |View|Graph selected Variables|Time Series Plot| and
choosing the two variables to be plotted. This does not produce a very
informative graph.

- Right clicking on the graph brings up a context box. Select the edit item to bring up a tabbed options box. First select the lines tab and change the axis for line 2 LYR to right axis. Next select the main, x-axis, y1-axis and y2-axis to add various other labels to the graph. Note that various other options are available. There is no problem trying these to see how you get on. You can use the options in the context box to save the graph in various formats.

R is a comprehensive statistical package. Base R package is available for download from http://www.r-project.org/. You will get a faster download if you choose a nearby mirror site. To install basic R simply run the install program. If you are working in 64-bit windows you can install both the 64-bit and 32-bit versions versions. If you are installing (or updating) R packages in Windows 7 start R as administrator (Right click on R icon on desktop and select "run as administrator"). The packages can then be installed or updated from within R.

Many modern statistical techniques become available in R long before they are available in commercial packages. The system is open to the extent that source code is available for all routines on CRAN (Comprehensive R Archive Network). Currently the system consists of a base package and over 3000 supplementary packages. To get an idea of the coverage of R for econometrics one might look at the CRAN task views for Econometrics, Time Series , Finance, and the Social Sciences. Various other task views available at http://cran.r-project.org/ indicate other areas that may be of interest to economists and econometricians.

One of the reasons that I use R because it is easier to do the hard things in R. It is probably true to say that, until one gets accustomed to R, it is harder to do the easier things in R. I would, therefore, recommend R to an experienced economist who wishes to use some routine or a variant of an existing routine that is not easily available in a standard package. It would also be useful to anyone who wished to obtain a deeper understanding of a particular routine or who wished to control some aspect of a process. However anyone I know that has mastered the steep learning curve of R finds it convenient to use for ordinary tasks. If you wish to learn R you might start by reading through

- David Ruppert.
*Statistics and Data Analysis for Financial Engineering*. Use R! Springer, 2010. ISBN: 978-1-4419-7786-1. - Paul S. P. Cowpertwait and Andrew Metcalfe.
*Introductory Time Series with R*. Springer Series in Statistics. Springer, 2009. ISBN: 978-0-387-88697-8. - Giovanni Petris, Sonia Petrone, and Patriza Campagnoli.
*Dynamic Linear Models with R*. Use R. Springer, 2009. ISBN: 978-0-387-77237-0. - Bernhard Pfaff.
*Analysis of Integrated and Cointegrated Time Series with R, Second Edition*. Springer, New York, 2nd edition, 2008. ISBN 978-0-387-75966-1. - Jonathan D. Cryer and Kung-Sik Chan.
*Time Series Analysis With Applications in R*. Springer, New York, 2008. ISBN 978-0-387-75958-6. - Hrishikesh D. Vinod.
*Hands-on Intermediate Econometrics Using R: Templates for Extending Dozens of Practical Examples*. World Scientific, Hackensack, NJ, 2008. - Christian Kleiber and Achim Zeileis.
*Applied Econometrics with R*. Springer, New York, 2008. ISBN 978-0-387-77316-2. - Robert H. Shumway and David S. Stoffer.
*Time Series Analysis and Its Applications With R Examples*. Springer, New York, 2006. ISBN 978-0-387-29317-2 (new edition now available ?)

If you are going to use R you need to use a program/script editor to write your program/script files. There is a simple editor included in the base R windows GUI (graphical user interface). Once you begin to do more advanced work you need a better development environment. Several are available at the moment. Currently I use RStudio and recommend it highly. The initial screen of RStudio is illustrated below.

Alternative R development environments include

- Emacs. My recommended site for Emacs for Windows is that maintained by Vincent Goulet. He distributes a version of Emacs that contains support for R, LaTeX, Octave and several other additions. I would not recommend Emacs to a new user of R as it is a bit different to the usual Windows programs.
- Tinn-R is a popular development for R that I have used in the past. Some people like it
- Rcmdr is a a platform-independent basic-statistics GUI (graphical user interface) for R which has been extended by a variety of plug-ins.
- Several other program development interfaces for R are described in http://sciviews.org/_rgui/.

- various tools for creating, transforming, editing time series
- Unit Root tests: ADF, HEGY (quarterly, monthly), Schmidt-Phillips, KPSS, Unit Root test with structural break
- Cointegration tests: Johansen Cointegration test with response surfaces, Saikkonen & Lütkepohl test
- kernel density estimation
- spectral density plots
- crossplots
- autocorrelation analysis

- VAR modelling (with arbitrary deterministic/exogenous variables)
- subset model estimation
- output in matrix form
- automatic model selection (various strategies based on information criteria)
- residual analysis with tests for non-normality, autocorrelation, ARCH, spectrum, kernel density, autocorrelation plots, crosscorrelation
- GARCH analysis for residuals
- Impulse Responses with bootstrapped confidence intervals also for accumulated responses, orthogonal and forecast error versions
- Forecast Error Variance Decomposition
- forecasting, also levels from 1st differences, asymptotic confidence intervals for levels
- causality tests
- stability analysis: bootstrapped Chow tests, recursive parameters, recursive residuals, CUSUM test
- SVAR modelling: AB model, Blanchard-Qua Model with bootstrapped standard errors
- SVAR Forecast Error Variance Decomposition
- SVAR Impulse Responses with bootstrapped confidence intervals

- VECM modelling (with arbitrary deterministic/exogenous variables)
- restrictions on cointegration space, Wald test for beta restrictions
- Johansen, Two Stage, S2S estimation procedures
- EC term can be fully or partly predetermined
- subset model estimation
- output in matrix form
- automatic model selection (various strategies based on information criteria)
- residual analysis with tests for nonnormality, autocorrelation, ARCH, spectrum, kernel density, autocorrelation plots, crosscorrelation
- Impulse Responses with bootstrapped confidence intervals also for accumulated responses, orthogonal and forecast error versions
- Forecast Error Variance Decomposition
- forecasting, also levels from 1st differences, asymptotic confidence intervals for levels
- causality tests
- stability analysis: bootstrapped Chow tests, recursive parameters, recursive eigenvalues
- SVEC modelling with bootstrapped standard errors
- SVEC Forecast Error Variance Decomposition
- SVEC Impulse Responses with bootstrapped confidence intervals

- univariate ARCH, GARCH, T-GARCH estimation with different error distributions
- residual analysis for ARCH residuals with robustified test for no remaining ARCH (S. Lundbergh, T. Teraesvirta), plotting of variance process, kernel density for residuals
- multivariate GARCH(1,1) estimation, residual analysis, plotting of variance process together with univariate estimates, kernel density for residuals

- STR model specification with exogenous/deterministic variables
- linearity tests
- STR estimation
- various specification tests for no remaining nonlinearity, nonnormality, no remaining serial dependency, parameter constancy
- various plots to check estimated model

- lag selection for univariate models based on linear and nonlinear selection criteria
- nonlinear estimation with configurable 3D plots
- residual analysis
- model selection for volatility process
- estimation of volatility process
- residual analysis for volatility estimation residuals

- lag selection for AR and MA parameters with Hannan-Rissanen procedure
- estimation with fixed regressors
- residual analysis
- ARCH modelling of residuals
- forecasting with fixed regressors

Octave is quite similar to Matlab so that most programs are easily portable between the two. Base Matlab programs will often run in Octave without any amendment. Octave version for Windows 3.2.4 may be downloaded from http://octave.sourceforge.net/. When I install Octave I generally follow the option to install all Octave-Forge toolboxes. These often correspond to various toolboxes in Matlab and provide additional functionality to that available in base Matlab.

Octave version 3.2.4 may be downloaded from http://www.gnu.org/software/octave/download.html. Use the Windows binaries from Octave Forge. (Cygwin binaries are also available but unless you are familiar with Cygwin I would not recommend them). I would recommend that you install Octave in a directory that has no embedded blanks (e.g. "c:\octave" rather than "c:\Program Files". I also install all Octave Forge toolboxes. This is equivalent to installing a lot of Matlab toolboxes and increases the functionality of the package. However it installs the oct2mat package which contains a bug which interferes with various plotting functions. The simple solution is to start Octave and issue the command

pkg rebuild -noauto oct2matand exit [Cntrl + D]. the next time you start Octave oct2mat will not be loaded and graphics will work. For more details see http://wiki.octave.org/wiki.pl?OctaveForWindows.

Much of my Matlab notes

Michael Creel has an econometrics text with applications implemented in Octave. This test is available in pdf and may be downloaded from http://idea.uab.es/~mcreel/.

The Matlab GUI is very good and is far ahead of that in Octave. The version of Octave mentioned here contains the editor Notepad++ which works but is not well integrated with Octave. (As of September, 2012 a new version of octave ( octave-3.6.2-vs2010-setup.exe) containg an preliminary version of a new Octave GUI is available. If you wish to use this be careful to follow the instructions in the readme file)

An implementation of the Linux GUI for Octave is available from http://www.outsch.org/2011/01/29/qtoctave-0-10-1-for-windows/. I have used this interface in Linux and it is good. I have also used the emacs interface to Octave but this is for emacs addicts.

- In step 1. the integral of 1/(1+x^3) is calculated
- In step 2. the derivative of the result is calculated

- In step 3. the result of the previous step is simplified
- In step 4. the definite integral from 0 to 1 is calculated.
- In step 5. the numerical value of this result is calculated.

The following description of LibreOffice is taken from http://www.libreoffice.org/features/.

**Writer** is
the word processor inside LibreOffice. Use it for everything, from
dashing off a quick letter to producing an entire book with tables of
contents, embedded illustrations, bibliographies and diagrams. The
while-you-type auto-completion, auto-formatting and automatic spelling
checking make difficult tasks easy (but are easy to disable if you
prefer). Writer is powerful enough to tackle desktop publishing tasks
such as creating multi-column newsletters and brochures. The only limit
is your imagination.

**Calc** tames
your numbers and helps with difficult decisions when you're weighing
the alternatives. Analyze your data with Calc and then use it to
present your final output. Charts and analysis tools help bring
transparency to your conclusions. A fully-integrated help system makes
easier work of entering complex formulas. Add data from external
databases such as SQL or Oracle, then sort and filter them to produce
statistical analyses. Use the graphing functions to display large
number of 2D and 3D graphics from 13 categories, including line, area,
bar, pie, X-Y, and net – with the dozens of variations available,
you're sure to find one that suits your project.

**Impress** is
the fastest and easiest way to create effective multimedia
presentations. Stunning animation and sensational special effects help
you convince your audience. Create presentations that look even more
professional than the standard presentations you commonly see at work.
Get your colleagues' and bosses' attention by creating something a
little bit different.

**Draw** lets
you build diagrams and sketches from scratch. A picture is worth a
thousand words, so why not try something simple with box and line
diagrams? Or else go further and easily build dynamic 3D illustrations
and special effects. It's as simple or as powerful as you want it to be.

**Base** is
the database front-end of the LibreOffice suite. With Base, you can
seamlessly integrate your existing database structures into the other
components of LibreOffice, or create an interface to use and administer
your data as a stand-alone application. You can use imported and linked
tables and queries from MySQL, PostgreSQL or Microsoft Access and
many other data sources, or design your own with Base, to build
powerful front-ends with sophisticated forms, reports and views.
Support is built-in or easily addable for a very wide range of database
products, notably the standardly-provided HSQL, MySQL, Adabas D,
Microsoft Access and PostgreSQL.

**Math** is
a simple equation editor that lets you lay-out and display your
mathematical, chemical, electrical or scientific equations quickly in
standard written notation. Even the most-complex calculations can be
understandable when displayed correctly. E=mc^{2}.

LibreOffice also comes configured with a PDF file creator, meaning you can distribute documents that you're sure can be opened and read by users of almost any computing device or operating system.

If one is working on a less powerful PC one might consider using gnumeric or abiword. gnumeric is a spreadsheet program that can read and write excel files and do many of the calculations that an economist might wish to do with a spreadsheet. In effect many of the statistical functions in gnumeric are more accurate than those in other spreadsheets.abiword is a relatively small word processor. Both of these packages can export files for use in LaTeX.

One sets out the structure of the document by listing the parts, chapters, sections, subsections etc. Within each part, section etc. one sets out in plain text and mark-up the content of the part, section etc. LaTeX then does all the formatting for you. (You can of course fine tune the results afterwards but this is often not necessary.)

In mathematics, engineering and physics LaTeX has become a de facto standard. Many thousands of books have been published using LaTeX. Many journals in these fields are produced using LaTeX.

Many publications in other fields, including economics, are also produced using LaTeX but it has not been as successful in these fields as in more technical fields because LaTeX was primarily designed for mathematics. If you are writing technical material then it is much easier to produce good output with LaTeX than with a word processor. If you have a lot of equations and graphs LaTeX is also quicker than a word processor. Latex can also produce tables of contents, lists of tables and lists of figures. It has a helper program (bibtex) that reads bibliographic material from a separate file and manages citations within the document and produces lists of references. This external file of bibliographic material can be managed by another helper program (Jabref) and can be extended and used for several documents.

The following is a small sample tex file. It is largely self explanatory. Any tex file consists of first a preamble and secondly the content of the document and its structure. The preamble here consists of the single \documentclass(article) statement. In general other auxiliary packages will be included here. If you are starting LaTeX I would advise that you get an appropriate preamble from a colleague. Don't worry if you don't understand it all in the beginning. If you have the bandwidth in your internet connection I would recommend the Protext TeX distribution. This is based on the Miktex TeX distribution but is a little easier to install. The install will take at least an hour and perhaps even more. To generate the .tex file you need a text editor. Do not even think of using a word processor. Several text editors have special facilities for editing .tex files. MikTeX installs the editor TeXworks by default. I would have a preference for another editor Texmaker which I think offers more help to a beginner. If a colleague uses another editor and is willing to give some help and advice then you should try his editor. Alternatively if you already use emacs then it has an excellent Tex mode, AucTeX.

% WARNING! Do not type any of the following 10 characters except as directed:

% & $ # % _ { } ^ ~ \

\documentclass{article} % Your input file must contain these two lines

\begin{document} % plus the \end{document} command at the end.

\section{Simple Text} % This command makes a section title.

Words are separated by one or more spaces. Paragraphs are separated by

one or more blank lines. The output is not affected by adding extra

spaces or extra blank lines to the input file.

Double quotes are typed like this: ``quoted text''.

Single quotes are typed like this: `single-quoted text'.

Long dashes are typed as three dash characters---like this.

Emphasized text is typed like this: \emph{this is emphasized}.

Bold text is typed like this: \textbf{this is bold}.

\subsection{A Warning or Two} % This command makes a subsection title.

If you get too much space after a mid-sentence period---abbreviations

like etc.\ are the common culprits)---then type a backslash followed by

a space after the period, as in this sentence.

Remember, don't type the 10 special characters (such as dollar sign and

backslash) except as directed! The following seven are printed by

typing a backslash in front of them: \$ \& \# \% \_ \{ and \}.

The manual tells how to make other symbols.

\end{document} % The input file ends with this command.

Loading this file into Texmaker and running TeX produces the pdf file below.

There is a good introduction to Latex on http://en.wikibooks.org/wiki/LaTeX. This book is available there in html, pdf and LaTeX source. Further material is listed at http://www.tug.org/begin.html and in the links there. If you going to write technical material in economics then an investment in LaTeX is worthwhile.

Lyx is an alternative Graphical interface to LaTeX which can be downloaded from http://www.lyx.org/.

- KompoZer is a complete web authoring system that combines web file management and easy-to-use WYSIWYG web page editing.
- KompoZer is designed to be extremely easy to use, making it ideal for non-technical computer users who want to create an attractive, professional-looking web site without needing to know HTML or web coding
- .Almost all of my web pages have been edited and set-up with Kompozer or the earlier Nvu.