## Gretl and Hansl — econometrics made easy

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

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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!

Paul

Comment by Paul O'Sullivan— 28 October, 2015 #

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!

Oleh

Comment by oleh— 10 November, 2015 #

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?

Comment by oleh— 12 November, 2015 #

Stay beautiful, Oleh. Stay beautiful.

Comment by pontus— 13 November, 2015 #

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

ARE NO IMPORTANT BUGS IN ESTIMATION

AND TESTING!!!

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)

THAT’S ALL!

(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

models

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!

Comment by oleh— 31 December, 2015 #

Use R!

Comment by Robert Norman— 15 April, 2016 #