econometricsmodels
A Python API providing statistical and econometric analysis methods. It is primarily intended for use as the analysis engine for economicon, a GUI application for data analysis, and its design prioritizes ease of embedding from scripts and programs (type completion, validation, dynamic construction).
- The computational core is implemented in Rust and thinly bound to Python via PyO3.
- Data input is restricted to polars DataFrames only, passed to the Rust side via Arrow zero-copy.
- Formula-string parsing (e.g.
y ~ x1 + x2) is not used. The dependent variable is passed as a single column name (str), independent variables as a list of column names (list[str]), and estimation options as an instance of a dedicated class.
Installation
pip install econometricsmodels
Requires Python 3.12 or later.
Quickstart
import polars as pl
from econometricsmodels import OLS
df = pl.DataFrame(
{
"y": [2.1, 3.9, 6.2, 8.1, 9.8],
"x1": [1.0, 2.0, 3.0, 4.0, 5.0],
}
)
result = OLS(df, y="y", x=["x1"]).fit()
print(result.params) # {"const": ..., "x1": ...}
print(result.std_errors) # {"const": ..., "x1": ...}
print(result.r_squared)
For more details — including how to switch to heteroskedasticity-robust standard errors (HC0-HC3), cluster-robust standard errors, and HAC (Newey-West) standard errors — see the documentation site. The full documentation, including the API reference, is published at https://masahiroyecon1997dev.github.io/econometricsmodels/.
Implementation status
Implemented: OLS (Ordinary Least Squares), WLS (Weighted Least Squares).
In progress: Logit.
Planned next, in this order: Probit → Tobit → IV (2SLS/GMM) → FE (Fixed Effects) → RE (Random Effects) → GLS.
During the 0.x.x pre-release period, breaking changes may occur even in minor version bumps.
Verification accuracy
Estimates for each implemented method (coefficients, standard errors, confidence intervals, R², adjusted R², AIC, BIC, log-likelihood, F-statistic, F-test p-value) are verified by numerical comparison against reference implementations. In addition to a primary reference, an independent implementation is used as a cross-check.
cov_type |
Primary reference | Independent cross-check |
|---|---|---|
| classical / HC0-3 / cluster | statsmodels (relative tolerance 1e-8) | R (lm/lm(weights=) + sandwich/lmtest, relative tolerance 1e-8) |
| HAC (Newey-West) | statsmodels (relative tolerance 1e-8) | R (relative tolerance 1e-2 for OLS, 5e-2 for WLS — looser due to differing small-sample correction conventions) |
License
1 maintainer
Metadata
1 maintainer
Release files for econometricsmodels 0.3.0
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Source distribution (sdist)
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|---|---|---|---|
| econometricsmodels-0.3.0.tar.gz | 187.9 kB | Details |
Built distributions (wheels)
Total release size: 68.7 MB
Release files / econometricsmodels-0.3.0.tar.gz
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