Gretl and Hansl — econometrics made easy

27 October, 2015 at 15:29 | Posted in Statistics & Econometrics | 6 Comments

Hansel-and-gretel-rackhamThanks to Allin Cottrell and Riccardo Lucchetti we today have access to a high quality tool for doing and teaching econometrics — Gretl.

And, best of all, it is totally free!

Gretl is up to the tasks you may have, so why spend money on expensive commercial programs?

The latest snapshot version of Gretl – 2015d – can be downloaded here.

With this new version also comes a handy primer on Hansl — the scripting language of Gretl.

So just go ahead. With Gretl and Hansl, econometrics has never been easier to master!




  1. I used Gretl as the required tool for the second of two undergraduate economics modules I took with the Open University in the UK. The first module, taken two years earlier, used SPSS. I found Gretl intuitive and straight forward.

    My introduction to econometrics was interesting and instructive. It has informed my reading and understanding of other peoples work since. Give it a try!


  2. Hansl language is a real bomb. It took me less than 3 weeks between
    writing the first lines and having the first official Gretl package approved!
    Another pleasant thing: I got to know Lars from Real-World Economics Review
    and I share Lars’ point of view. Now I know he likes Gretl too!

  3. Econometrics as debunking (© Steve Keen) tool
    A couple of examples
    Neglected theorems on random walk
    1) if a random walk exists infinitely long it’s distribution is not a distribution of a proper random variable: it’s +-Infty with p=1/2
    Consequence for “efficient” market hypothesis
    In the long run stock indexes go to zero or explode → even efficient markest should be regulated

    2) Mean time of intersecting a given horizontal line is infinite → stock indexes can go off any fundamentals for infinitely long and can differ by infinitely large

    Neglected consequence of Hall(1978): under rational expectations income and consumption are not cointegrated! What can be more absurd!

    Beveridge-Nelson decomposition and RBC
    so, under “efficient” markets we have and independent source for random walk
    under rational expectations we have a second independent random walk for consumption
    The third source is “native”: technical progress is integrated

    So, if a macroeconomy should be described as VECM with k variables, the maximal cointegration rank is k-3. But it follows from multivariate Beverage-Nelson decomposition that for RBC model to be described as VECM it should have k-1 cointegration rank with the only independent random walk for technical progress. That is why there are no financial sector in RBC models.

    Another interesting neglected theorem on random walk: in R^d, d>2, random walk is not recurrent at all!
    We have just seen we have at minimum 3 independent random walks in a macroeconomic system even under fantastic neoclassical information assumptions!

    P.S. I work as an econometric instructor, but I have PhD in probability, so as a “child” I was taught
    a different set of theorems in a stochastic processes course.

    They like to blame heterodox economists in neglecting math, but what kind of mathematicians are they themselves?

  4. Stay beautiful, Oleh. Stay beautiful.

  5. Gretl is clearly underestimated.
    Now I’ll make a modest attempt to correct it.
    1) Use by serious organizations: Gretl is known
    to be used by Bank of Brazil and saves them a lot
    of money.
    2) A myth in that Gretl is buggy. Really, one
    can not very rare bump into small bug
    in saving plots in exotic formats etc., or
    easy to find a way around bugs while Hansl
    scripting. And Allin & Riccardo are
    fantastically quick in correcting. AND THERE
    3) Gretl has the simplest and the most intuitive
    GUI ever seen! Unfortunately, enormous
    percentage of Universities have only one
    semester of econometrics. Gretl is
    absolutely the best to teach some greens
    something useful for such inadequate time
    4) Hansl!!! For example, how to clone
    mathlab’s feval:

    function scalar feval (string fun, scalar x)
    return @ fun
    end function
    usage: feval(“sin(x)”,$pi/4)

    (stiff data types, copy-past and
    create for vectors in 2 seconds)

    5) New models: Gretl have
    mle, gmm, and simulated annealing,
    also very easy syntax to bootstrap your
    6) GUI creation
    You write a function, go to the package GUI
    editor and in a couple of dozens of seconds
    you’ll have the same nice looking menu item
    for you function as a native command has!

    7) Speed. S language (R is “GNU S”) is very nice,
    but if you can’t do C, C++, or ancient Fortrant
    your cool code will be a snail. If you use
    hansl, you needn’t learn Rcpp package.
    Many people (I also) use hansl for
    Monte-Carlo studies.

    8) R integration. For, example, Rob Hyndman
    wrote the best thing for univariate time series
    models, {forecast} {R}. I simply wrote Gretl
    interface to it. Since Gretl is GNU, as Rob wrote
    everything I should do is to give a proper refence
    to him.
    9) Do not contrast R and Gretl. Your marginal
    expenses are Zero. INTEGRATE THEM!
    10) Happy New Year!
    11) Happy Gretl!

  6. Use R!

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