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v0.29.0

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@s3alfisc s3alfisc released this 18 Apr 11:50
· 20 commits to master since this release
6eb5150

PyFixest 0.29

Highlights

  • The most important news is that we have overhauled PyFixest's small sample corrections, which now 100% match r-fixest! By default, r-fixest and py-fixest standard errors should now match all of the time. If they don't, please reach out to us, chances are that you've found a bug =) Because it took me a significant amount of time to figure out how fixest handles small sample corrections, we have added a note in which I summarize my understanding here: link.
  • We have added support for fully saturated difference-in-differences modeling (the Sun-Abraham approach to event studies), including functions for aggregating treatment effects to the cohort level. You can find examples in the DiD-vignette: link
  • This in turn allows us to support @apoorvalal's event-study specification test, which may help you decide if you can get away with a simple two-way fixed effects specification for your event study. If you haven't yet seen Apoorva's paper, you can find it on arxiv.
  • After I've failed to run a Gelbach decomposition for a work problem on industry scale data, we've overhauled its internals - the entire decomposition is now computed on sparse matrices, with drastic performance improvements.

All Changes

New Contributors

Full Changelog: v0.27.1...v0.29.0