Matteo Courthoud

Data Scientist, Economist, Researcher. Like = bookmark.

[Alex Fischer @s3alfisc]

On citing research software - I really appreciate what @davidroodman is doing in the abstract of his papers.

It's just a quick footnote but makes sure that the people supporting the software behind his research are recognized!

@ArielKarlinsky @VincentAB @soodoku

[Jimbo Brand @jamesbrandecon]

I'm looking for an economics (or related) PhD intern to work with me at Microsoft (in Seattle) for the summer! If you're interested in building new causal inference tools and have interest/experience in tech, IO, and/or econometrics, please reach out!

[Matteo Courthoud @MatteoCourthoud]

@EgorHowell Thanks! Let's see first if I manage to keep it going consistently and people are interested

[Matteo Courthoud @MatteoCourthoud]

Hi all!

I am trying something new: a weekly list of my causal inference reads, new and old stuff. I guess you could call it a newsletter, but it's rather a commitment device for me. Still, I hope it can be useful to others as well.

Enjoy! 🤗

https://t.co/MEHOG6Kv9O

[Matteo Courthoud @MatteoCourthoud]

@pietrobiroli Thanks a lot Pietro for the shout out! A warning: my guide is from a couple of years ago now and I havent checked new versions of the underlying theme.

My recommendation atm is to go for Google sites, unless you are a bit of a UX design nerd (have some HTML and CSS knowledge)

[Lihua Lei @lihua_lei_stat]

@jmwooldridge Naming is to blame. Why do we call Gaussian GLM “linear regression” but poisson GLM “poisson regression”? We should probably rename poisson reg as something like “exponential reg” (and logistic reg as “expit reg”, etc)

[Matteo Courthoud @MatteoCourthoud]

@edesouza15 Amazing! Will add it ASAP!

[Matteo Courthoud @MatteoCourthoud]

Hi all!

I just collected a lot of causal inference resources in a single repo. It contains books, lectures, software, blogs, papers, ... It's still a work in progress, but happy if anyone wants to collaborate! Enjoy 🤗

https://t.co/AMmIZfPQXC

[Matteo Courthoud @MatteoCourthoud]

@valeriolondee Absolutely! Though, by now it grew so large it's quite impractical https://t.co/ipwqJ1Z4PE

[Peng Ding @pengding00]

My lecture notes on causal inference

[Matt Blackwell @matt_blackwell]

After a long and unsuccessful search for a statistical inference and regression textbook at the right level for our PhD students, I finally decided to write up my lecture notes as a book.

The book is publicly available if you are interested:

https://t.co/XDB34FjaMS

[Peter Hull @instrumenthull]

I'm teaching a new grad applied metrics course this spring; inspired by @paulgp, I've decided to post slides here

First, Ch. 1-3: a review of regression basics and discussions of design- & model-based ID

https://t.co/cwCKVACoXN

https://t.co/VMkU8V78hQ

https://t.co/iEOWLwTYQz

[apoorva.lal @Apoorva__Lal]

3 years ago, I took my methods comprehensive exam just as everything was shutting down.

To prep, I made a cheatsheet that quickly got out of hand and now stands at ~130 pages of notes on econometrics / causal inference / machine learning.

https://t.co/t6qkZ9B30A

[Jimbo Brand @jamesbrandecon]

I'm looking for a summer intern to work with me and @demirermert to study firms' cloud computing productivity/efficiency using a large (many TB) and unique dataset. Please apply and if you do, please also send me your CV at both emails on my website https://t.co/d9WRRf6o8r

[Matteo Courthoud @MatteoCourthoud]

@AsjadNaqvi Totally! Great list Asjad!

[Matteo Courthoud @MatteoCourthoud]

New post out!

I have been asked many times for resources to approach or study causal inference, so I collected all the *free* resources I know in a single place. It is a very personal list, related to my background and areas of expertise. Enjoy! 🤗

https://t.co/xrylzvekLl

[Matteo Courthoud @MatteoCourthoud]

StableDiffusion is an incredible tool to generate article covers. Styling plots as paintings is a pleasure for the eye and a great satisfaction for people with no artistic skills (me). Here is a restyled cover of one of my old articles on @TDataScience

https://t.co/KqxglfXd4a

[Matteo Courthoud @MatteoCourthoud]

@joannasakowska Thank you! I'm so glad it was helpful!

[Matheus Facure Alves @MatheusFacure]

Double/Debiased ML (Chernozhukov et al, 2016) is a fascinating tool for CATE estimation. Although the theory is pretty intuitive, I think few appreciate what it is really doing, so here is a visual guide for. 🧵
TL;DR, Double-ML can be viewed as a derivative finder.

[Paolo Mengano @Paolo_Mengano]

Hi #EconTwitter!

I am on the #EconJobMarket this year. Time for a thread about my JMP.

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