Lectures in Quantitative Economics with Python [pdf]
lectures.quantecon.org
lectures.quantecon.org
While it's true that Economic Sciences prize is not a "real" Nobel prize, it is commonly referred to as a Nobel prize. Interestingly, the Nobel Foundation also lists "Economic Sciences" on their website listing Nobel prizes even though they do not award or fund it: https://www.nobelprize.org/prizes/
If you're coming from an ML-focused approach to statistics, studying econometrics can be an interesting change of pace, because the focus is totally different. ML practicioners tend to be focused on prediction, while econometricians tend to focus on causal inference - utilizing pseudo-experimental variation within the data to estimate causal effects between variables. This turns out to be really hard to do correctly, and learning the pitfalls can make it easy to identify potential weaknesses in other research.
Most econometric work has historically been done in Stata, although it seems like both R and Python have been increasing in prominence a bit recently.
In Stata's defense: It helps that Stata is actually really good for the "running regressions" part. In particular, it gets robust standard errors right without much extra work in complex cases that would require a lot of additional code in Python or R.
R wins easily for data visualization and scripting, though. It's also much better as a skill you can "take with you". If you end up working in industry, you may not be able to expense a Stata license, but you'll almost certainly be able to use R (although maybe not RStudio).
I’ve written so much documentation on Confluence where it would have been easier to just send a pdf like this :/
I often wish R's syntax was cleaner and faster, Julia is may accomplish this. I don't think Python is a great substitute for R in many areas where statistic is heavily used and influenced. I've used Python for Deep Learning and NLP. Time series and many other statistical base stuff I use R.
Edit: I agree that the "...more interesting" comment above sounds condescending. I have not found the Julia community to be condescending.
But it's certainly hard sometimes for people who learned of powerful non mainstream languages, having to see people putting an amazing amount of resources and effort to provide every functionality to mainstream less powerful languages that would be almost free in said powerful language (be it syntax extensions with macros, high performance dynamic code without using FFI, parallelism, better compile-time checking...). It's probably what Lisp users had to deal with for 60 years now. Or more recently people who learned Rust but still have to deal with a world of C++.
I am not a Julia programmer, I mostly write in python, but I find their community welcoming and not condescending at all. I think it would have a positive impact on most people’s personality
The language is very interesting too but doesn’t yet have a google, apple or msft behind it so I would understand why lovers of it maybe overstep a little promoting to try to keep it alive
Personally I find the integration with cuda to be really well done and I could see it being easier than python for highly customized deep learning (custom kernels etc)
Your comment above seems kind of unnecessarily mean spirited to me - maybe I’m reading it wrong?
I was surprised - because I remember you responding to the “I made 500k with machine learning guy” and being really impressed with your willingness to try to teach the guy without shitting on him (I’m an ex algo/hft guy and think someone with your knowledge could have gone that route very easily)
Anyone who wants to learn, great. Anyone who wants a one-sentence snark, I'm not going to be as open to helping out.
I remember thinking about this before I knew JULIA. I can't remember that time clearly. I have tried to black it out. Presumably, I was just sitting nude in a cave bashing two rocks together covered in faeces and confused shame...just like you.
Here are things I can guarantee: learning JULIA will make you stronger, more agile, your IQ will double, women will be able to smell your dominance, children will run from you screaming in terror, you will be able to grow a thick lustrous beard (even if you are a woman), you will be able to talk to animals and lead them in battle, and you will be able to throw a spear through a 5m deep concrete wall from 200m.
EDIT: I forgot, if you do learn JULIA be sure to avoid any contact with indigenous societies. They will likely think you are a God. You go to the Amazon one time, and suddenly these people are building shrines, making human sacrifices, and carving intricate wood etchings of benchmarks and terse, readable function compositions (they told me they were still using Python2.7...lol).
I've always loved the questions economics asks, but found the methodology for finding answers to miss out on ideas from computer science
There's also a (very challenging, I would guess 150-300 hours time commitment) MIT course online: https://ocw.mit.edu/courses/mathematics/18-06sc-linear-algeb... But it has videos.
I would focus on Chapter 21 in the pdf because it tells you exactly what you need for this application. And supplement it as needed.
You mean optimization techniques that don't work in the real world of finance?
And economists have been writing code since PL/1.