fereg (Python)
Fast high-dimensional fixed-effects regressions with pyfixest-compatible syntax and results.
fereg.feols, fereg.fepois and fereg.feglm take pyfixest 0.60.0's formulas, arguments and
defaults and return results with pyfixest's classes, names and methods, so estimates, standard
errors and statistics match pyfixest's. The estimation runs in a parallel Rust core that
eliminates the largest fixed effect exactly and solves the others by preconditioned conjugate
gradient: at 10 million observations and 16 threads it is 5–100× faster than pyfixest and
2–200× faster than R's fixest on the fixest benchmark designs.
import fereg
m = fereg.feols("y ~ x1 + x2 | firm + year", data=df, vcov={"CRV1": "firm"})
iv = fereg.feols("y ~ x1 | firm + year | x2 ~ z", data=df)
p = fereg.fepois("count ~ x1 | firm + year", data=df, vcov="hetero")
lg = fereg.feglm("default ~ x1 | firm", data=df, family="logit")
m.summary()
fereg.etable([m, iv, p], type="md")
m.fixef()
Supported: OLS, IV/2SLS (several endogenous regressors), Poisson, logit; any number of fixed
effects, fe1^fe2 interactions and varying slopes fe[x]; weights; i(), C(), multiple
estimation (sw, csw, several left-hand sides, split/fsplit); predict, resid,
fixef, tidy, etable. Data can be pandas or polars.
Variances (vcov= at estimation, or post hoc with m.vcov(...)), as in pyfixest with ssc():
"iid", "hetero"/"HC1", "HC2", "HC3"; {"CRV1": "a+b"} and {"CRV3": "a+b"} (up to
four-way); Newey–West "NW" and Driscoll–Kraay "DK" with
vcov_kwargs={"time_id": "year", "panel_id": "firm", "lag": 2}. fereg extensions (pyfixest
raises): HC2/HC3 with fixed effects, CRV3 for IV and logit (logit refits), Newey–West /
Driscoll–Kraay for IV and Driscoll–Kraay without panel_id, and fixest's Conley spatial HAC:
vcov="conley", vcov_kwargs={"lat": "lat", "lon": "lon", "cutoff": "100km"} (cutoff in km
or "60mi", default deduced as fixest; pixel, distance="triangular"|"spherical").
Not implemented: probit; nid variances (raise NotImplementedError); wild bootstrap,
ccv, decompose, ritest, plotting and DiD helpers.
Formulas can use functions and objects from the caller through pyfixest's context=
(context=0: the calling frame; an int k: k frames further up; a mapping: the names it
gives; default None: none), e.g. fereg.feols("y ~ f(x) | firm", df, context={"f": f}).
Separation checks as in pyfixest (separation_check=["fe"] by default, "ir"; every GLM
family, models with fixed effects only), with its warning "N observations removed because of
separation.". Deliberate differences from pyfixest 0.60.0: gaussian feglm iid variances are
scaled by the residual variance (pyfixest's Feglm._vcov_iid fixes the dispersion at 1), and
the "ir" check also works after rows were dropped before it (pyfixest's misaligns its
predictions then and drops nothing).
nthreads (default: all cores) sets the number of threads. Results do not depend on it.
The same core powers the Stata commands fereg/feppml/felogit and the R package fereg:
see https://github.com/leoliu0/fereg.
1 maintainer
Metadata
1 maintainer
Release files for fereg 0.4.1
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Transparency logRelease files / fereg-0.4.1-cp311-cp311-macosx_11_0_arm64.whl
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Transparency logRelease files / fereg-0.4.1-cp311-cp311-macosx_10_12_x86_64.whl
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Transparency logRelease files / fereg-0.4.1-cp310-cp310-win_amd64.whl
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Transparency logRelease files / fereg-0.4.1-cp310-cp310-manylinux_2_28_x86_64.whl
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Transparency logRelease files / fereg-0.4.1-cp310-cp310-manylinux_2_28_aarch64.whl
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| Size | 3.0 MB |
| Tags | CPython 3.10 Linux glibc 2.28+ ARM64 |
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Transparency logRelease files / fereg-0.4.1-cp310-cp310-macosx_11_0_arm64.whl
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Transparency logRelease files / fereg-0.4.1-cp310-cp310-macosx_10_12_x86_64.whl
| Download URL | fereg-0.4.1-cp310-cp310-macosx_10_12_x86_64.whl |
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| Size | 3.4 MB |
| Tags | CPython 3.10 macOS 10.12+ x86-64 |
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Transparency logSecurity for fereg 0.4.1
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