
Economics Nobel laureate Paul Romer is a Python programming convert - okket
https://qz.com/1417145/economics-nobel-laureate-paul-romer-is-a-python-programming-convert/
======
21
> _he tried to use Mathematica to share one of his studies in a way that
> anyone could explore every detail of his data and methods. It didn’t work.
> He says that Mathematica’s owner, Wolfram Research, made it too difficult to
> share his work in a way that didn’t require other people to use the
> proprietary software, too_

Sometimes I wonder where Mathematica would be if it were open sourced lets say
in 2010. It had such a head start over Python.

Interestingly, Mathematica interop with Python is basically non-existent
today, even worse than it was in the past. Short term moat building destroying
long term viability.

~~~
hellogoodbyeeee
I loved using Mathematica in college. It was the first programming language I
ever really used to make some cool things. I wish it was more accessible. I
think one of the requirements of my dream job would be a work place that uses
Mathematica.

It's really fun reading through "code golf" challenges where other languages
take 10-15 lines for something that Mathematica has a built in for.

~~~
SonOfLilit
Did you just say "code golf" and Mathematica in the same sentence?

Then you will love these. I own like 10 copies, which I give to people for
their birthdays: [http://adereth.github.io/blog/2017/11/02/playing-with-
wolfra...](http://adereth.github.io/blog/2017/11/02/playing-with-wolfram-
playing-cards/)

~~~
owenversteeg
Oh, those are quite cool. I'll have to get a pack sometime. I also think the
Executed Today deck looks pretty cool (totally different card subject)

------
daxat_staglatz
People interested by the use of Python in economic research should check out
QuantEcon [0], a project to develop tools and courses for computational
economics [1] in Python and Julia

[0] [https://quantecon.org/](https://quantecon.org/)

[1] A fancy expression to say "using programming to solve economic models"

~~~
FabHK
Yeah, and Economics Nobel laureate Thomas Sargent is a Julia programming
convert (he even gave the JuliaCon 2016 keynote, video embedded below:)

[https://juliacomputing.com/case-studies/thomas-
sargent.html](https://juliacomputing.com/case-studies/thomas-sargent.html)

EDIT to add: I should say that Thomas Sargent is one of the founders of
QuantEcon (cited by OP), that's why I'm bringing this up here.

Another resource on Julia in Computational Economics:

[https://juliaeconomics.com](https://juliaeconomics.com)

------
mxuribe
Beyond the cool python angle, I find the following statement quite
interesting: "...James Somers argued that Jupyter notebooks may replace the
traditional research paper typically shared as a PDF..." I've only been
exposed to jupyter notebook references here and there...but i guess i should
become a little more familiar with them.

~~~
AlanSE
While I think this is a good thing, an additional requirement is needed. The
published notebook should be sequentially executed by an automated tool. Users
can execute commands out of order and have artifacts from deleted commands.
Without verification, you can be publishing notebooks with bugs in them that
you don't see until you re-execute them.

~~~
dunpeal
Jupyter notebooks are ultimately just a text file, which can be version
controlled, verified (via the VCS or independent hashing), and if necessary -
digitally signed in a cryptographically secure manner.

Given that Git is already secure, I'd say all the researcher needs to know is
basic usage of Git. Version controlling the notebook satisfies all the
requirements you mentioned: prevents accidental distortion, is verifiable,
restorable, etc.

~~~
21
You forget that a typical Python Jupyter notebook will import a dozen Python
packages.

Versioning that it's still a major problem in the ecosystem.

~~~
dunpeal
> Versioning that it's still a major problem in the ecosystem.

There's actually a perfectly good way to solve this problem: a virtual
environment with a requirements.txt file.

~~~
LyndsySimon
For research in particular, I'd suggest a Pipfile.lock. That will ensure that
the packages installed match exactly, not just by version number.

------
patagonia
Someone should point him toward SageMath.

The article’s title is misleading. Doesn’t sound like he is a Python convert.
Sounds like he is an open source tool convert.

------
lellotope
Am I missing something or are parts of this article really distorted?

For example, this seems to set up most of the article:

"Economics involves a lot of math and statistics. The most commonly used tools
to crunch numbers are the spreadsheet software Microsoft Excel and programming
languages Stata and Mathematica."

Is this really true? Mathematica and Stata seem like established but niche
products to me at this point. I wouldn't say either of them are "the most
commonly used tools to crunch numbers."

If you asked me to predict what a quantitative economist would be using, it
would be Python, followed by R, and maybe followed by Java or C, or something
like that.

This was an interesting article in the sense I like learning these sorts of
things about people, but the premise seemed off to me.

But I'm not an economist so maybe this is something about economics per se.

~~~
prepend
“If you asked me to predict what a quantitative economist would be using, it
would be Python, followed by R, and maybe followed by Java or C, or something
like that.”

I too was looking for good data. It’s hard to measure this as practical
application doesn’t line up with publication.

I was surprised when I started working in health 10 years ago that the
predominant tool was Excel, and then SAS. Even 5 years ago in health grad
school, they only taught SAS.

This is slowly changing to R and python, but general data analysis skills is
less than basic engineering stuff 20 years ago.

~~~
xapata
Some departments in the FDA require clinical trial data to be submitted in SAS
formats :-/

~~~
robterrin
This is a myth: [http://blog.revolutionanalytics.com/2012/06/fda-r-
ok.html](http://blog.revolutionanalytics.com/2012/06/fda-r-ok.html)

[https://www.fda.gov/downloads/forindustry/datastandards/stud...](https://www.fda.gov/downloads/forindustry/datastandards/studydatastandards/ucm587506.pdf)

~~~
xapata
No, by the text of that same link you provided: "... origin of this fallacy is
probably related to the fact that data must be submitted in the XPT "transport
format" (which was originally created by SAS)." While that post goes on to
say, "This [XPT] data format is now an open standard." That is somewhat
disingenuous. The XPT format requires IBM Mainframe floats and other
wierdness. It's not always that easy to write XPT.

------
nycticorax
Does anyone have any insight into why Paul Romer is a Julia skeptic?

In the blog post

[https://paulromer.net/jupyter-mathematica-and-the-future-
of-...](https://paulromer.net/jupyter-mathematica-and-the-future-of-the-
research-paper/)

he says:

"Which reminds me. If you are a Julia enthusiast, how do you suppose the
investors in this new language plan to make their big score?"

Also there's this:

[https://twitter.com/paulmromer/status/985507319114096640](https://twitter.com/paulmromer/status/985507319114096640)

It doesn't seem like he's followed up on his threat/promise to write a blog
post about why he's not a Julia enthusiast, however.

------
notfromhere
There's probably a lot of gnashing of teeth over this article at
WRI/Mathematica.

~~~
copperx
As long as it makes Stephen Wolfram angry, I'm happy.

~~~
notfromhere
If you're a former employee, you know he is.

------
TorKlingberg
I'm surprised there seems to be have been no HN discussion on this years
Economics prize. Or are my HS search skills lacking?

~~~
daxat_staglatz
I haven't found any, either.

This is a shame because economics is already a computational discipline and
increasingly so. It can be of interest to the HN crowd.

There is an awful lot of programming done by people that are not professional
programmers. As an economist myself, I think code have become so central to
our profession that we can no longer afford to ignore software engineering
best practices. Conversely, there may be quite a few topics in computational
economics that interest programmers.

For instance, an awful lot of macroeconomics - including to an extent Romer's
sub-field, endogenous growth theory - is essentially programming in Dynare [0]
and doing computer simulations.

Nordhaus got the prize for developing (quite basic, actually) simulation
models that integrate the economic systems and environmental systems. See for
instance there [1].

Micro-simulation is of course a big area where programming and economics meet
- you can follow development on github [2, 3]. This is code that has an
enormous impact on society, as it is used as a basis to evaluate the effects
of policies.

Econometrics, aka statistics for economics, is also a big area where
programmers could contribute to economic research. There is a big push to
adapt ML techniques to solve economists' problems, eg Athey's research [4].

[0] [http://www.dynare.org/](http://www.dynare.org/)

[1] [https://sites.google.com/site/williamdnordhaus/dice-
rice](https://sites.google.com/site/williamdnordhaus/dice-rice)

[2] [https://github.com/openfisca](https://github.com/openfisca)

[3]
[https://github.com/InseeFr/Destinie-2](https://github.com/InseeFr/Destinie-2)

[4] [https://arxiv.org/abs/1510.04342](https://arxiv.org/abs/1510.04342)

~~~
nl
This is a great comment.

I believe the NY Fed has open source economic models in Julia, too.

~~~
daxat_staglatz
Indeed : [https://github.com/FRBNY-DSGE/DSGE.jl](https://github.com/FRBNY-
DSGE/DSGE.jl)

------
agumonkey
Next one will be a Julia convert.

~~~
okket
According to this comment further down there already is one:

[https://news.ycombinator.com/item?id=18174769](https://news.ycombinator.com/item?id=18174769)

------
varjag
But Python 2 or Python 3?

~~~
waivek
The Turing complete one.

------
tragomaskhalos
I use Python and it's OK, but I find a lot of the breathless hype around it
_as a language_ a little baffling as there are more than an average number of
stupidities in there. However this piece is really around exploiting the
amazing infrastructure that has built up around Python that empowers
mathematical and statistical research, which is fair enough.

~~~
dunpeal
What are these "stupidities" that bother you?

Personally, I use Python a lot for anything related to data science. No
language is perfect, but I'd say Python has a lot less deficiencies and warts
than most other mainstream languages, and it's extremely well suited for tasks
in data science and related fields such as machine learning.

The main issue with Python is that its default platform (CPython) isn't very
efficient. That's not a problem in the language itself; in fact, it's partly
caused by all the benefits of a high-level language: you simply don't have the
same facilities to optimize your resource consumption as you do in, say, Rust.

The upside is of course that the code is far more concise and readable.

~~~
Insanity
Whilst that is true, for data science related things I end up using Pandas
(and Numpy) often which are fast.

So most of the heavy lifting is not done by python itself.

~~~
mynewtb
So what? Pandas and numpy are still use with Python code using their APIs. The
implementation details are not something the users care about. They write
Python.

~~~
dunpeal
Not sure what you're arguing. If you use numpy and pandas properly, most of
your computations happen in optimized C routines.

So you will write Python, but get very good resource (both time and space)
efficiency.

