Name | pyfixest JSON |
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Summary | Fast high dimensional fixed effect estimation following syntax of the fixest R package. |
upload_time | 2024-12-15 12:43:39 |
maintainer | None |
docs_url | None |
author | Styfen SchΓ€r |
requires_python | >=3.9 |
license | MIT |
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![](figures/pyfixest-logo.png)
# PyFixest: Fast High-Dimensional Fixed Effects Regression in Python
[![License](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/license/mit)
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[![image](https://codecov.io/gh/py-econometrics/pyfixest/branch/master/graph/badge.svg)](https://codecov.io/gh/py-econometrics/pyfixest)
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[![Downloads](https://static.pepy.tech/badge/pyfixest)](https://pepy.tech/project/pyfixest)
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[pixi-url]: https://pixi.sh
`PyFixest` is a Python implementation of the formidable [fixest](https://github.com/lrberge/fixest) package for fast high-dimensional fixed effects regression.
The package aims to mimic `fixest` syntax and functionality as closely as Python allows: if you know `fixest` well, the goal is that you won't have to read the docs to get started! In particular, this means that all of `fixest's` defaults are mirrored by `PyFixest` - currently with only [one small exception](https://github.com/py-econometrics/pyfixest/issues/260).
Nevertheless, for a quick introduction, you can take a look at the [documentation](https://py-econometrics.github.io/pyfixest/pyfixest.html) or the regression chapter of [Arthur Turrell's](https://github.com/aeturrell) book on [Coding for Economists](https://aeturrell.github.io/coding-for-economists/econmt-regression.html#imports).
For questions on `PyFixest`, head on over to our [PyFixest Discourse forum](https://pyfixest.discourse.group/).
## Features
- **OLS**, **WLS** and **IV** Regression
- **Poisson Regression** following the [pplmhdfe algorithm](https://journals.sagepub.com/doi/full/10.1177/1536867X20909691)
- Multiple Estimation Syntax
- Several **Robust** and **Cluster Robust Variance-Covariance** Estimators
- **Wild Cluster Bootstrap** Inference (via
[wildboottest](https://github.com/py-econometrics/wildboottest))
- **Difference-in-Differences** Estimators:
- The canonical Two-Way Fixed Effects Estimator
- [Gardner's two-stage
("`Did2s`")](https://jrgcmu.github.io/2sdd_current.pdf)
estimator
- Basic Versions of the Local Projections estimator following
[Dube et al (2023)](https://www.nber.org/papers/w31184)
- **Multiple Hypothesis Corrections** following the Procedure by [Romano and Wolf](https://journals.sagepub.com/doi/pdf/10.1177/1536867X20976314) and **Simultaneous Confidence Intervals** using a **Multiplier Bootstrap**
- Fast **Randomization Inference** as in the [ritest Stata package](https://hesss.org/ritest.pdf)
- The **Causal Cluster Variance Estimator (CCV)** following [Abadie et al.](https://economics.mit.edu/sites/default/files/2022-09/When%20Should%20You%20Adjust%20Standard%20Errors%20for%20Clustering.pdf)
- Regression **Decomposition** following [Gelbach (2016)](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1425737)
- **Publication-ready tables** with [Great Tables](https://posit-dev.github.io/great-tables/articles/intro.html) or LaTex booktabs
## Installation
You can install the release version from `PyPI` by running
```py
# inside an active virtual environment
python -m pip install pyfixest
```
or the development version from github by running
```py
python -m pip install git+https://github.com/py-econometrics/pyfixest
```
## Benchmarks
All benchmarks follow the [fixest
benchmarks](https://github.com/lrberge/fixest/tree/master/_BENCHMARK).
All non-pyfixest timings are taken from the `fixest` benchmarks.
![](benchmarks/lets-plot-images/benchmarks_ols.svg)
![](benchmarks/lets-plot-images/benchmarks_poisson.svg)
## Quickstart
```python
import pyfixest as pf
data = pf.get_data()
pf.feols("Y ~ X1 | f1 + f2", data=data).summary()
```
###
Estimation: OLS
Dep. var.: Y, Fixed effects: f1+f2
Inference: CRV1
Observations: 997
| Coefficient | Estimate | Std. Error | t value | Pr(>|t|) | 2.5% | 97.5% |
|:--------------|-----------:|-------------:|----------:|-----------:|-------:|--------:|
| X1 | -0.919 | 0.065 | -14.057 | 0.000 | -1.053 | -0.786 |
---
RMSE: 1.441 R2: 0.609 R2 Within: 0.2
### Multiple Estimation
You can estimate multiple models at once by using [multiple estimation
syntax](https://aeturrell.github.io/coding-for-economists/econmt-regression.html#multiple-regression-models):
```python
# OLS Estimation: estimate multiple models at once
fit = pf.feols("Y + Y2 ~X1 | csw0(f1, f2)", data = data, vcov = {'CRV1':'group_id'})
# Print the results
fit.etable()
```
est1 est2 est3 est4 est5 est6
------------ ----------------- ----------------- ----------------- ----------------- ----------------- -----------------
depvar Y Y2 Y Y2 Y Y2
------------------------------------------------------------------------------------------------------------------------------
Intercept 0.919*** (0.121) 1.064*** (0.232)
X1 -1.000*** (0.117) -1.322*** (0.211) -0.949*** (0.087) -1.266*** (0.212) -0.919*** (0.069) -1.228*** (0.194)
------------------------------------------------------------------------------------------------------------------------------
f2 - - - - x x
f1 - - x x x x
------------------------------------------------------------------------------------------------------------------------------
R2 0.123 0.037 0.437 0.115 0.609 0.168
S.E. type by: group_id by: group_id by: group_id by: group_id by: group_id by: group_id
Observations 998 999 997 998 997 998
------------------------------------------------------------------------------------------------------------------------------
Significance levels: * p < 0.05, ** p < 0.01, *** p < 0.001
Format of coefficient cell:
Coefficient (Std. Error)
### Adjust Standard Errors "on-the-fly"
Standard Errors can be adjusted after estimation, "on-the-fly":
```python
fit1 = fit.fetch_model(0)
fit1.vcov("hetero").summary()
```
Model: Y~X1
###
Estimation: OLS
Dep. var.: Y
Inference: hetero
Observations: 998
| Coefficient | Estimate | Std. Error | t value | Pr(>|t|) | 2.5% | 97.5% |
|:--------------|-----------:|-------------:|----------:|-----------:|-------:|--------:|
| Intercept | 0.919 | 0.112 | 8.223 | 0.000 | 0.699 | 1.138 |
| X1 | -1.000 | 0.082 | -12.134 | 0.000 | -1.162 | -0.838 |
---
RMSE: 2.158 R2: 0.123
### Poisson Regression via `fepois()`
You can estimate Poisson Regressions via the `fepois()` function:
```python
poisson_data = pf.get_data(model = "Fepois")
pf.fepois("Y ~ X1 + X2 | f1 + f2", data = poisson_data).summary()
```
###
Estimation: Poisson
Dep. var.: Y, Fixed effects: f1+f2
Inference: CRV1
Observations: 997
| Coefficient | Estimate | Std. Error | t value | Pr(>|t|) | 2.5% | 97.5% |
|:--------------|-----------:|-------------:|----------:|-----------:|-------:|--------:|
| X1 | -0.007 | 0.035 | -0.190 | 0.850 | -0.075 | 0.062 |
| X2 | -0.015 | 0.010 | -1.449 | 0.147 | -0.035 | 0.005 |
---
Deviance: 1068.169
### IV Estimation via three-part formulas
Last, `PyFixest` also supports IV estimation via three part formula
syntax:
```python
fit_iv = pf.feols("Y ~ 1 | f1 | X1 ~ Z1", data = data)
fit_iv.summary()
```
###
Estimation: IV
Dep. var.: Y, Fixed effects: f1
Inference: CRV1
Observations: 997
| Coefficient | Estimate | Std. Error | t value | Pr(>|t|) | 2.5% | 97.5% |
|:--------------|-----------:|-------------:|----------:|-----------:|-------:|--------:|
| X1 | -1.025 | 0.115 | -8.930 | 0.000 | -1.259 | -0.790 |
---
## Call for Contributions
Thanks for showing interest in contributing to `pyfixest`! We appreciate all
contributions and constructive feedback, whether that be reporting bugs, requesting
new features, or suggesting improvements to documentation.
If you'd like to get involved, but are not yet sure how, please feel free to send us an [email](alexander-fischer1801@t-online.de). Some familiarity with
either Python or econometrics will help, but you really don't need to be a `numpy` core developer or have published in [Econometrica](https://onlinelibrary.wiley.com/journal/14680262) =) We'd be more than happy to invest time to help you get started!
## Contributors β¨
Thanks goes to these wonderful people:
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"description": "![](figures/pyfixest-logo.png)\n\n# PyFixest: Fast High-Dimensional Fixed Effects Regression in Python\n\n[![License](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/license/mit)\n![PyPI - Python Version](https://img.shields.io/pypi/pyversions/pyfixest.svg)\n[![PyPI -Version](https://img.shields.io/pypi/v/pyfixest.svg)](https://pypi.org/project/pyfixest/)\n[![image](https://codecov.io/gh/py-econometrics/pyfixest/branch/master/graph/badge.svg)](https://codecov.io/gh/py-econometrics/pyfixest)\n[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)\n[![Pixi Badge][pixi-badge]][pixi-url]\n[![All Contributors](https://img.shields.io/badge/all_contributors-18-green.svg?style=flat-square)](#contributors-)\n[![Downloads](https://static.pepy.tech/badge/pyfixest)](https://pepy.tech/project/pyfixest)\n[![Downloads](https://static.pepy.tech/badge/pyfixest/month)](https://pepy.tech/project/pyfixest)\n\n[pixi-badge]:https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/prefix-dev/pixi/main/assets/badge/v0.json&style=flat-square\n[pixi-url]: https://pixi.sh\n\n`PyFixest` is a Python implementation of the formidable [fixest](https://github.com/lrberge/fixest) package for fast high-dimensional fixed effects regression.\n\nThe package aims to mimic `fixest` syntax and functionality as closely as Python allows: if you know `fixest` well, the goal is that you won't have to read the docs to get started! In particular, this means that all of `fixest's` defaults are mirrored by `PyFixest` - currently with only [one small exception](https://github.com/py-econometrics/pyfixest/issues/260).\n\nNevertheless, for a quick introduction, you can take a look at the [documentation](https://py-econometrics.github.io/pyfixest/pyfixest.html) or the regression chapter of [Arthur Turrell's](https://github.com/aeturrell) book on [Coding for Economists](https://aeturrell.github.io/coding-for-economists/econmt-regression.html#imports).\n\nFor questions on `PyFixest`, head on over to our [PyFixest Discourse forum](https://pyfixest.discourse.group/).\n\n## Features\n\n- **OLS**, **WLS** and **IV** Regression\n- **Poisson Regression** following the [pplmhdfe algorithm](https://journals.sagepub.com/doi/full/10.1177/1536867X20909691)\n- Multiple Estimation Syntax\n- Several **Robust** and **Cluster Robust Variance-Covariance** Estimators\n- **Wild Cluster Bootstrap** Inference (via\n [wildboottest](https://github.com/py-econometrics/wildboottest))\n- **Difference-in-Differences** Estimators:\n - The canonical Two-Way Fixed Effects Estimator\n - [Gardner's two-stage\n (\"`Did2s`\")](https://jrgcmu.github.io/2sdd_current.pdf)\n estimator\n - Basic Versions of the Local Projections estimator following\n [Dube et al (2023)](https://www.nber.org/papers/w31184)\n- **Multiple Hypothesis Corrections** following the Procedure by [Romano and Wolf](https://journals.sagepub.com/doi/pdf/10.1177/1536867X20976314) and **Simultaneous Confidence Intervals** using a **Multiplier Bootstrap**\n- Fast **Randomization Inference** as in the [ritest Stata package](https://hesss.org/ritest.pdf)\n- The **Causal Cluster Variance Estimator (CCV)** following [Abadie et al.](https://economics.mit.edu/sites/default/files/2022-09/When%20Should%20You%20Adjust%20Standard%20Errors%20for%20Clustering.pdf)\n- Regression **Decomposition** following [Gelbach (2016)](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1425737)\n- **Publication-ready tables** with [Great Tables](https://posit-dev.github.io/great-tables/articles/intro.html) or LaTex booktabs\n\n\n## Installation\n\nYou can install the release version from `PyPI` by running\n\n```py\n# inside an active virtual environment\npython -m pip install pyfixest\n```\n\nor the development version from github by running\n\n```py\npython -m pip install git+https://github.com/py-econometrics/pyfixest\n```\n\n## Benchmarks\n\nAll benchmarks follow the [fixest\nbenchmarks](https://github.com/lrberge/fixest/tree/master/_BENCHMARK).\nAll non-pyfixest timings are taken from the `fixest` benchmarks.\n\n![](benchmarks/lets-plot-images/benchmarks_ols.svg)\n![](benchmarks/lets-plot-images/benchmarks_poisson.svg)\n\n## Quickstart\n\n\n```python\nimport pyfixest as pf\n\ndata = pf.get_data()\npf.feols(\"Y ~ X1 | f1 + f2\", data=data).summary()\n```\n\n ###\n\n Estimation: OLS\n Dep. var.: Y, Fixed effects: f1+f2\n Inference: CRV1\n Observations: 997\n\n | Coefficient | Estimate | Std. Error | t value | Pr(>|t|) | 2.5% | 97.5% |\n |:--------------|-----------:|-------------:|----------:|-----------:|-------:|--------:|\n | X1 | -0.919 | 0.065 | -14.057 | 0.000 | -1.053 | -0.786 |\n ---\n RMSE: 1.441 R2: 0.609 R2 Within: 0.2\n\n\n### Multiple Estimation\n\nYou can estimate multiple models at once by using [multiple estimation\nsyntax](https://aeturrell.github.io/coding-for-economists/econmt-regression.html#multiple-regression-models):\n\n\n\n```python\n# OLS Estimation: estimate multiple models at once\nfit = pf.feols(\"Y + Y2 ~X1 | csw0(f1, f2)\", data = data, vcov = {'CRV1':'group_id'})\n# Print the results\nfit.etable()\n```\n\n est1 est2 est3 est4 est5 est6\n ------------ ----------------- ----------------- ----------------- ----------------- ----------------- -----------------\n depvar Y Y2 Y Y2 Y Y2\n ------------------------------------------------------------------------------------------------------------------------------\n Intercept 0.919*** (0.121) 1.064*** (0.232)\n X1 -1.000*** (0.117) -1.322*** (0.211) -0.949*** (0.087) -1.266*** (0.212) -0.919*** (0.069) -1.228*** (0.194)\n ------------------------------------------------------------------------------------------------------------------------------\n f2 - - - - x x\n f1 - - x x x x\n ------------------------------------------------------------------------------------------------------------------------------\n R2 0.123 0.037 0.437 0.115 0.609 0.168\n S.E. type by: group_id by: group_id by: group_id by: group_id by: group_id by: group_id\n Observations 998 999 997 998 997 998\n ------------------------------------------------------------------------------------------------------------------------------\n Significance levels: * p < 0.05, ** p < 0.01, *** p < 0.001\n Format of coefficient cell:\n Coefficient (Std. Error)\n\n\n\n\n### Adjust Standard Errors \"on-the-fly\"\n\nStandard Errors can be adjusted after estimation, \"on-the-fly\":\n\n\n```python\nfit1 = fit.fetch_model(0)\nfit1.vcov(\"hetero\").summary()\n```\n\n Model: Y~X1\n ###\n\n Estimation: OLS\n Dep. var.: Y\n Inference: hetero\n Observations: 998\n\n | Coefficient | Estimate | Std. Error | t value | Pr(>|t|) | 2.5% | 97.5% |\n |:--------------|-----------:|-------------:|----------:|-----------:|-------:|--------:|\n | Intercept | 0.919 | 0.112 | 8.223 | 0.000 | 0.699 | 1.138 |\n | X1 | -1.000 | 0.082 | -12.134 | 0.000 | -1.162 | -0.838 |\n ---\n RMSE: 2.158 R2: 0.123\n\n\n### Poisson Regression via `fepois()`\n\nYou can estimate Poisson Regressions via the `fepois()` function:\n\n\n```python\npoisson_data = pf.get_data(model = \"Fepois\")\npf.fepois(\"Y ~ X1 + X2 | f1 + f2\", data = poisson_data).summary()\n```\n\n ###\n\n Estimation: Poisson\n Dep. var.: Y, Fixed effects: f1+f2\n Inference: CRV1\n Observations: 997\n\n | Coefficient | Estimate | Std. Error | t value | Pr(>|t|) | 2.5% | 97.5% |\n |:--------------|-----------:|-------------:|----------:|-----------:|-------:|--------:|\n | X1 | -0.007 | 0.035 | -0.190 | 0.850 | -0.075 | 0.062 |\n | X2 | -0.015 | 0.010 | -1.449 | 0.147 | -0.035 | 0.005 |\n ---\n Deviance: 1068.169\n\n\n### IV Estimation via three-part formulas\n\nLast, `PyFixest` also supports IV estimation via three part formula\nsyntax:\n\n\n```python\nfit_iv = pf.feols(\"Y ~ 1 | f1 | X1 ~ Z1\", data = data)\nfit_iv.summary()\n```\n\n ###\n\n Estimation: IV\n Dep. var.: Y, Fixed effects: f1\n Inference: CRV1\n Observations: 997\n\n | Coefficient | Estimate | Std. Error | t value | Pr(>|t|) | 2.5% | 97.5% |\n |:--------------|-----------:|-------------:|----------:|-----------:|-------:|--------:|\n | X1 | -1.025 | 0.115 | -8.930 | 0.000 | -1.259 | -0.790 |\n ---\n\n## Call for Contributions\n\nThanks for showing interest in contributing to `pyfixest`! We appreciate all\ncontributions and constructive feedback, whether that be reporting bugs, requesting\nnew features, or suggesting improvements to documentation.\n\nIf you'd like to get involved, but are not yet sure how, please feel free to send us an [email](alexander-fischer1801@t-online.de). Some familiarity with\neither Python or econometrics will help, but you really don't need to be a `numpy` core developer or have published in [Econometrica](https://onlinelibrary.wiley.com/journal/14680262) =) We'd be more than happy to invest time to help you get started!\n\n## Contributors \u2728\n\nThanks goes to these wonderful people:\n\n<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->\n<!-- prettier-ignore-start -->\n<!-- markdownlint-disable -->\n<table>\n <tbody>\n <tr>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://github.com/styfenschaer\"><img src=\"https://avatars.githubusercontent.com/u/79762922?v=4?s=100\" width=\"100px;\" alt=\"styfenschaer\"/><br /><sub><b>styfenschaer</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=styfenschaer\" title=\"Code\">\ud83d\udcbb</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://www.nkeleher.com/\"><img src=\"https://avatars.githubusercontent.com/u/5607589?v=4?s=100\" width=\"100px;\" alt=\"Niall Keleher\"/><br /><sub><b>Niall Keleher</b></sub></a><br /><a href=\"#infra-NKeleher\" title=\"Infrastructure (Hosting, Build-Tools, etc)\">\ud83d\ude87</a> <a href=\"https://github.com/py-econometrics/pyfixest/commits?author=NKeleher\" title=\"Code\">\ud83d\udcbb</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"http://wenzhi-ding.com\"><img src=\"https://avatars.githubusercontent.com/u/30380959?v=4?s=100\" width=\"100px;\" alt=\"Wenzhi Ding\"/><br /><sub><b>Wenzhi Ding</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=Wenzhi-Ding\" title=\"Code\">\ud83d\udcbb</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://apoorvalal.github.io/\"><img src=\"https://avatars.githubusercontent.com/u/12086926?v=4?s=100\" width=\"100px;\" alt=\"Apoorva Lal\"/><br /><sub><b>Apoorva Lal</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=apoorvalal\" title=\"Code\">\ud83d\udcbb</a> <a href=\"https://github.com/py-econometrics/pyfixest/issues?q=author%3Aapoorvalal\" title=\"Bug reports\">\ud83d\udc1b</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://juanitorduz.github.io\"><img src=\"https://avatars.githubusercontent.com/u/22996444?v=4?s=100\" width=\"100px;\" alt=\"Juan Orduz\"/><br /><sub><b>Juan Orduz</b></sub></a><br /><a href=\"#infra-juanitorduz\" title=\"Infrastructure (Hosting, Build-Tools, etc)\">\ud83d\ude87</a> <a href=\"https://github.com/py-econometrics/pyfixest/commits?author=juanitorduz\" title=\"Code\">\ud83d\udcbb</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://s3alfisc.github.io/\"><img src=\"https://avatars.githubusercontent.com/u/19531450?v=4?s=100\" width=\"100px;\" alt=\"Alexander Fischer\"/><br /><sub><b>Alexander Fischer</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=s3alfisc\" title=\"Code\">\ud83d\udcbb</a> <a href=\"#infra-s3alfisc\" title=\"Infrastructure (Hosting, Build-Tools, etc)\">\ud83d\ude87</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"http://www.aeturrell.com\"><img src=\"https://avatars.githubusercontent.com/u/11294320?v=4?s=100\" width=\"100px;\" alt=\"aeturrell\"/><br /><sub><b>aeturrell</b></sub></a><br /><a href=\"#tutorial-aeturrell\" title=\"Tutorials\">\u2705</a> <a href=\"https://github.com/py-econometrics/pyfixest/commits?author=aeturrell\" title=\"Documentation\">\ud83d\udcd6</a> <a href=\"#promotion-aeturrell\" title=\"Promotion\">\ud83d\udce3</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://github.com/leostimpfle\"><img src=\"https://avatars.githubusercontent.com/u/31652181?v=4?s=100\" width=\"100px;\" alt=\"leostimpfle\"/><br /><sub><b>leostimpfle</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=leostimpfle\" title=\"Code\">\ud83d\udcbb</a> <a href=\"https://github.com/py-econometrics/pyfixest/issues?q=author%3Aleostimpfle\" title=\"Bug reports\">\ud83d\udc1b</a></td>\n </tr>\n <tr>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://github.com/baggiponte\"><img src=\"https://avatars.githubusercontent.com/u/57922983?v=4?s=100\" width=\"100px;\" alt=\"baggiponte\"/><br /><sub><b>baggiponte</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=baggiponte\" title=\"Documentation\">\ud83d\udcd6</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://github.com/sanskriti2005\"><img src=\"https://avatars.githubusercontent.com/u/150411024?v=4?s=100\" width=\"100px;\" alt=\"Sanskriti\"/><br /><sub><b>Sanskriti</b></sub></a><br /><a href=\"#infra-sanskriti2005\" title=\"Infrastructure (Hosting, Build-Tools, etc)\">\ud83d\ude87</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://github.com/Jayhyung\"><img src=\"https://avatars.githubusercontent.com/u/40373774?v=4?s=100\" width=\"100px;\" alt=\"Jaehyung\"/><br /><sub><b>Jaehyung</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=Jayhyung\" title=\"Code\">\ud83d\udcbb</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"http://alexstephenson.me\"><img src=\"https://avatars.githubusercontent.com/u/24926205?v=4?s=100\" width=\"100px;\" alt=\"Alex\"/><br /><sub><b>Alex</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=asteves\" title=\"Documentation\">\ud83d\udcd6</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://github.com/greenguy33\"><img src=\"https://avatars.githubusercontent.com/u/8525718?v=4?s=100\" width=\"100px;\" alt=\"Hayden Freedman\"/><br /><sub><b>Hayden Freedman</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=greenguy33\" title=\"Code\">\ud83d\udcbb</a> <a href=\"https://github.com/py-econometrics/pyfixest/commits?author=greenguy33\" title=\"Documentation\">\ud83d\udcd6</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://github.com/saidamir\"><img src=\"https://avatars.githubusercontent.com/u/20246711?v=4?s=100\" width=\"100px;\" alt=\"Aziz Mamatov\"/><br /><sub><b>Aziz Mamatov</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=saidamir\" title=\"Code\">\ud83d\udcbb</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://github.com/rafimikail\"><img src=\"https://avatars.githubusercontent.com/u/61386867?v=4?s=100\" width=\"100px;\" alt=\"rafimikail\"/><br /><sub><b>rafimikail</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=rafimikail\" title=\"Code\">\ud83d\udcbb</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://www.linkedin.com/in/benjamin-knight/\"><img src=\"https://avatars.githubusercontent.com/u/12180931?v=4?s=100\" width=\"100px;\" alt=\"Benjamin Knight\"/><br /><sub><b>Benjamin Knight</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=b-knight\" title=\"Code\">\ud83d\udcbb</a></td>\n </tr>\n <tr>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://dsliwka.github.io/\"><img src=\"https://avatars.githubusercontent.com/u/49401450?v=4?s=100\" width=\"100px;\" alt=\"Dirk Sliwka\"/><br /><sub><b>Dirk Sliwka</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=dsliwka\" title=\"Code\">\ud83d\udcbb</a> <a href=\"https://github.com/py-econometrics/pyfixest/commits?author=dsliwka\" title=\"Documentation\">\ud83d\udcd6</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://github.com/daltonm-bls\"><img src=\"https://avatars.githubusercontent.com/u/78225214?v=4?s=100\" width=\"100px;\" alt=\"daltonm-bls\"/><br /><sub><b>daltonm-bls</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/issues?q=author%3Adaltonm-bls\" title=\"Bug reports\">\ud83d\udc1b</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://github.com/marcandre259\"><img src=\"https://avatars.githubusercontent.com/u/19809475?v=4?s=100\" width=\"100px;\" alt=\"Marc-Andr\u00e9\"/><br /><sub><b>Marc-Andr\u00e9</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=marcandre259\" title=\"Code\">\ud83d\udcbb</a> <a href=\"https://github.com/py-econometrics/pyfixest/issues?q=author%3Amarcandre259\" title=\"Bug reports\">\ud83d\udc1b</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://github.com/kylebutts\"><img src=\"https://avatars.githubusercontent.com/u/19961439?v=4?s=100\" width=\"100px;\" alt=\"Kyle F Butts\"/><br /><sub><b>Kyle F Butts</b></sub></a><br /><a href=\"#data-kylebutts\" title=\"Data\">\ud83d\udd23</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://fosstodon.org/@marcogorelli\"><img src=\"https://avatars.githubusercontent.com/u/33491632?v=4?s=100\" width=\"100px;\" alt=\"Marco Edward Gorelli\"/><br /><sub><b>Marco Edward Gorelli</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/pulls?q=is%3Apr+reviewed-by%3AMarcoGorelli\" title=\"Reviewed Pull Requests\">\ud83d\udc40</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"http://arelbundock.com\"><img src=\"https://avatars.githubusercontent.com/u/987057?v=4?s=100\" width=\"100px;\" alt=\"Vincent Arel-Bundock\"/><br /><sub><b>Vincent Arel-Bundock</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=vincentarelbundock\" title=\"Code\">\ud83d\udcbb</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://github.com/IshwaraHegde97\"><img src=\"https://avatars.githubusercontent.com/u/187858441?v=4?s=100\" width=\"100px;\" alt=\"IshwaraHegde97\"/><br /><sub><b>IshwaraHegde97</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=IshwaraHegde97\" title=\"Code\">\ud83d\udcbb</a></td>\n <td align=\"center\" valign=\"top\" width=\"12.5%\"><a href=\"https://github.com/RoyalTS\"><img src=\"https://avatars.githubusercontent.com/u/702580?v=4?s=100\" width=\"100px;\" alt=\"Tobias Schmidt\"/><br /><sub><b>Tobias Schmidt</b></sub></a><br /><a href=\"https://github.com/py-econometrics/pyfixest/commits?author=RoyalTS\" title=\"Documentation\">\ud83d\udcd6</a></td>\n </tr>\n </tbody>\n</table>\n\n<!-- markdownlint-restore -->\n<!-- prettier-ignore-end -->\n\n<!-- ALL-CONTRIBUTORS-LIST:END -->\n\nThis project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind welcome!\n",
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