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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.21749 |
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| _version_ | 1866914441492168704 |
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| author | Bergé, Laurent R. Butts, Kyle McDermott, Grant |
| author_facet | Bergé, Laurent R. Butts, Kyle McDermott, Grant |
| contents | fixest is an R package for fast and flexible econometric estimation. It provides a unified framework for applied research, with comprehensive support for a diverse class of models: ordinary least squares, instrumental variables, generalized linear models, maximum likelihood, and difference-in-differences. The package particularly excels at fixed-effects estimation, supported by a novel fixed-point acceleration algorithm implemented in C++. This algorithm achieves rapid convergence across a variety of data contexts and enables efficient estimation of complex models, including those with varying slopes. An expressive formula interface facilitates multiple estimations, stepwise regressions, and variable interpolation in a single call. Users can adjust inference strategies on the fly, choosing from an array of built-in robust standard errors. The package also provides methods for publication-ready regression tables and coefficient plots. Benchmarks demonstrate that fixest offers best-in-class performance against leading alternatives in R, PYTHON, and JULIA. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_21749 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | fixest: A fast and feature-rich framework for econometric estimations in R Bergé, Laurent R. Butts, Kyle McDermott, Grant Econometrics fixest is an R package for fast and flexible econometric estimation. It provides a unified framework for applied research, with comprehensive support for a diverse class of models: ordinary least squares, instrumental variables, generalized linear models, maximum likelihood, and difference-in-differences. The package particularly excels at fixed-effects estimation, supported by a novel fixed-point acceleration algorithm implemented in C++. This algorithm achieves rapid convergence across a variety of data contexts and enables efficient estimation of complex models, including those with varying slopes. An expressive formula interface facilitates multiple estimations, stepwise regressions, and variable interpolation in a single call. Users can adjust inference strategies on the fly, choosing from an array of built-in robust standard errors. The package also provides methods for publication-ready regression tables and coefficient plots. Benchmarks demonstrate that fixest offers best-in-class performance against leading alternatives in R, PYTHON, and JULIA. |
| title | fixest: A fast and feature-rich framework for econometric estimations in R |
| topic | Econometrics |
| url | https://arxiv.org/abs/2601.21749 |