Admittedly, this was 99% Dirk's work, so all praise should go to him =)

Btw, also works with Stata! py-econometrics.github.io/maketables/d...

@gaborbekes.bsky.social @arthurturrell.bsky.social @vincentab.bsky.social

Looking forward to the follow-up post on fixed effects in GLMs =)

Sorry for all the linkedin post, they just transfer you to the docs / github (I posted on lk first).

- You can find the full changelog here: lnkd.in/eEdzuVvq
- PyFixest on github: lnkd.in/eJRtm_rz
- maketables on github: lnkd.in/eYhAejYh

It currently supports pf and sm. Please check it out and contribute by adding support for your favorite Python estimation classes! Some that we think would be of interest: linearmodels, lifelines, Bambi, rdrobust, DoubleML, meta learners. You can find the package here: lnkd.in/eYhAejYh

We believe that there is a lot of value to unlock by providing a "𝗺𝗲𝘁𝗮 𝗿𝗲𝗴𝗿𝗲𝘀𝘀𝗶𝗼𝗻 𝘁𝗮𝗯𝗹𝗲" package for the Python scientific eco-system similar to what R has in 𝗺𝗼𝗱𝗲𝗹𝘀𝘂𝗺𝗺𝗮𝗿𝘆. So we have spun out PyFixest's etable functionalities into a standalone package, 𝗺𝗮𝗸𝗲𝘁𝗮𝗯𝗹𝗲𝘀.

This strategy is quite amenable to be run on the GPU - for "hard" problems where the alternating projections algorithm struggles to converge, running the demeaning on a 𝗚𝗣𝗨 can provide orders of magnitude of speedups.

We've added 𝗮𝗻𝗼𝘁𝗵𝗲𝗿 𝗯𝗮𝗰𝗸 end for 𝗱𝗲𝗺𝗲𝗮𝗻𝗶𝗻𝗴 𝗳𝗶𝘅𝗲𝗱 𝗲𝗳𝗳𝗲𝗰𝘁𝘀: instead of demeaning via the alternating projections algorithm, the new back end implements the Frisch-Waugh-Lovell theorem directly on 𝘀𝗽𝗮𝗿𝘀𝗲 𝗺𝗮𝘁𝗿𝗶𝗰𝗲𝘀.

We now support time series, panel 𝗛𝗔𝗖 and DK 𝘀𝘁𝗮𝗻𝗱𝗮𝗿𝗱 𝗲𝗿𝗿𝗼𝗿𝘀 (which was one of the most requested features, so I am very happy we have it now). It was also a very challenging PR, with very-tricky to debug numpy multi threading floating point errors.

First, a couple of weeks ago, the 𝗳𝗶𝘅𝗲𝘀𝘁 dev team released 𝟬.𝟭𝟯, which comes with a 𝗳𝗲𝘄 𝘀𝗺𝗮𝗹𝗹𝗲𝗿 𝗯𝗿𝗲𝗮𝗸𝗶𝗻𝗴 𝗰𝗵𝗮𝗻𝗴𝗲𝘀. We have decided to 𝗳𝗼𝗹𝗹𝗼𝘄 𝘀𝘂𝗶𝘁 and adjust PyFixest accordingly. The most important change is that by default, all standard errors are "iid".

Oh interesting, this does not look good. For me everything has been working well, I just upgraded to the newest fixest release via conda-forge a few weeks ago without any problems (as it happens, on windows!).

No global R or Python installation needed! And if you have these, no interference with your global installations.

Big fan. pixi.sh/latest/

Next step is to rewrite the vignette (more to the point & I need to make a better case for the methods usefulness in business contexts).

Also works with "negative" effects: