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Lectures in Quantitative Economics with Python [pdf]
- misrab 7y agoFINALLY the field of Economics is waking up to the 20th (yes) century... I've always loved the questions economics asks, but found the methodology for finding answers to miss out on ideas from computer science
- idonotknowwhy 7y agoI got lost at part 1.4.1 on page 6. I know python, but what would I need to learn to actually follow this pdf?
- fs100 7y agolooks like linear algebra
- idonotknowwhy 7y agoThanks, I'll hit youtube over the weekend
- WilliamEdward 7y agoi recommend this series https://www.youtube.com/watch?v=fNk_zzaMoSs https://www.youtube.com/watch?v=fNk_zzaMoSs
- idonotknowwhy 7y agoThanks, I'll check it out. This is one of those things which I never knew I didn't know about.
- rohan_shah 7y agoGoes very well with your username.
- psv1 7y agoI would recommend 3blue1brown only if you've already covered the material in another way. It's a great way to get some new intuition about things, the videos can help something 'click' and are a pleasant watch with an obviously high production quality. I just don't think they are great for being your first exposure to a topic.
- _edo 7y agoChapter 21 in the attached pdf gives a brief overview. 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-algebra-fall-2011/ 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.
- WilliamEdward 7y agoSome mathematics background would help. It is a book about quantitative economics after all.
- QuesnayJr 7y agoIt basically assumes you have at least one year's grad school level background in economics. It does give some overview, but probably not enough to learn it from the book alone.
- James_Henry 7y agoNo, this is advanced undergrad economics or at the most it is in the first year of grad school.
- codesushi42 7y agoWhich ideas from CS? You mean optimization techniques that don't work in the real world of finance?
- rohan_shah 7y agoEven though finance and economics overlap, I think that comment was referring to the social and psychological side of economics.
- codesushi42 7y agoWas it? Because I have no clue what the poster was referring to. And economists have been writing code since PL/1.
- AffineStructure 7y agohttps://en.wikipedia.org/wiki/Wassily_Leontief#Affiliation_with_Harvard https://en.wikipedia.org/wiki/Wassily_Leontief#Affiliation_w... . <- 1949 from Leontief
- Mikeb85 7y agoEcon has used maths and computers for a long time.
- zwaps 7y agoEh, these authors have been doing computational books for years in econ
- michael_j_ward 7y agoIf you want more than the PDF- here's the site: https://lectures.quantecon.org https://lectures.quantecon.org
- dash2 7y agoJust to point out: the co-author is Thomas Sargent, Nobel Prize winner and generally a big deal. If he's taught himself Python, then kudos (he's 76). Even if not, it's a strong recommendation to have his name on the cover.
- Lutzb 7y agoHe did not win a Nobel prize, as there is no such thing for economics. However he won the Nobel Memorial Prize in Economic Sciences.
- kchoudhu 7y agoYou must be great at parties.
- em500 7y agoHe's Dick, from the internet. https://dilbert.com/strip/2015-04-02 https://dilbert.com/strip/2015-04-02
- mjohn 7y agoI don't think pedantry about the name is a useful contribution to the conversation. 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/ https://www.nobelprize.org/prizes/
- Lutzb 7y agoThere is no conversation here. I was merely taking the opportunity to point out that there is a common misconception regarding the "Nobel prize" and the Nobel Memorial Prize in Economic Sciences. Two distinct prizes, one commonly mislabeled. Repeating the misnomer just normalizes the error.
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- xvilka 7y agoThey also have a Julia version, which is more interesting.
- miketery 7y agoAs someone with zero exposure to Julia can you provide some reasoning for why? (Honest question)
- anthony_doan 7y agoOne of the thing I like from Julia compare to Python is that it have the concept of missing data representation. Python's data science library represent it via NaN or Null which is good enough for most cases but not all cases. 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.
- chrispeel 7y agoQuick answer: Julia is often faster than Python and other high-level languages. Rather than writing high-level code in Python, R, or Matlab and performance-critical code in C, the idea is that one writes the whole thing in Julia. Edit: I agree that the "...more interesting" comment above sounds condescending. I have not found the Julia community to be condescending.
- kolbe 7y agoI want to learn Julia but I have a very big concern: does it actually alter your personality in a way that makes you condescend to everyone about their inferior programming languages, or is it just that people who already are condescending choose to learn Julia?
- hogFeast 7y agoHaha, this is a great question. 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).
- cwal37 7y agoAhh, this is nice. I work in an office with a number of economists (energy economics consulting firm), but I’m basically the only python user. Feel like this could be useful in bridging some gaps for the folks who only use SAS and got their PhDs cobbling together whatever code (VB, FOTRAN, etc.) got their models to run back in the day. I’ve written so much documentation on Confluence where it would have been easier to just send a pdf like this :/
- Quequau 7y agoThey also made the same lecture only using Julia rather than Python. I personally found it to be really useful and I taught myself enough Julia to be a danger to myself and others. https://lectures.quantecon.org/jl/ https://lectures.quantecon.org/jl/
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- alexhutcheson 7y agoIf you're interested in econometrics, I highly recommend checking out Marc Bellemare's "Metrics Mondays" blog posts, which are full of useful, pragmatic advice for applying econometric methods to real-world data: http://marcfbellemare.com/wordpress/metrics-mondays http://marcfbellemare.com/wordpress/metrics-mondays. 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.
- joker3 7y agoWhen I was in school around 2010 or so, a lot of the younger econ grad students were primarily interested in R. I don't think Stata's going away any time soon, but it might not be completely dominant for that much longer.
- lusmd 7y agoA lot of people I know at various departments are switching their undergrad stats/econometrics classes from Stata to R. That's the beginning of the end of Stata.
- joker3 7y agoThat matters, but I don't think that's happening until all of the big graduate-level metrics textbooks get R versions. And even then, at least a few papers are going to run into trouble with older reviewers who are used to seeing work done in Stata and don't trust anything else.
- alexhutcheson 7y ago