lfe: Linear Group Fixed Effects

Transforms away factors with many levels prior to doing an OLS. Useful for estimating linear models with multiple group fixed effects, and for estimating linear models which uses factors with many levels as pure control variables. See Gaure (2013) <doi:10.1016/j.csda.2013.03.024> Includes support for instrumental variables, conditional F statistics for weak instruments, robust and multi-way clustered standard errors, as well as limited mobility bias correction (Gaure 2014 <doi:10.1002/sta4.68>). WARNING: This package is NOT under active development anymore, no further improvements are to be expected, and the package is at risk of being removed from CRAN.

Version: 2.9-0
Depends: R (≥ 2.15.2), Matrix (≥ 1.1-2)
Imports: Formula, xtable, compiler, utils, methods, sandwich, parallel
Suggests: knitr, digest, igraph, plm, cubature (≥ 2.0.3), numDeriv, data.table, alpaca, testthat
Published: 2023-02-13
Author: Simen Gaure ORCID iD [aut], Grant McDermott [ctb], Mauricio Vargas ORCID iD [ctb], Karl Dunkle Werner [ctb], Matthieu Stigler ORCID iD [ctb, cre], Daniel L├╝decke [ctb]
Maintainer: Matthieu Stigler <Matthieu.Stigler at gmail.com>
BugReports: https://github.com/MatthieuStigler/lfe/issues
License: Artistic-2.0
Copyright: 2011-2019, Simen Gaure
URL: https://github.com/MatthieuStigler/lfe
NeedsCompilation: yes
Classification/JEL: C13, C23, C60
Classification/MSC: 62J05, 65F10, 65F50
Citation: lfe citation info
Materials: README NEWS
In views: Econometrics
CRAN checks: lfe results


Reference manual: lfe.pdf
Vignettes: Limited mobility bias correction
Multicollinearity, identification, and estimable functions
How lfe works
Convergence rate with examples


Package source: lfe_2.9-0.tar.gz
Windows binaries: r-devel: lfe_2.9-0.zip, r-release: lfe_2.9-0.zip, r-oldrel: lfe_2.9-0.zip
macOS binaries: r-release (arm64): lfe_2.9-0.tgz, r-oldrel (arm64): lfe_2.9-0.tgz, r-release (x86_64): lfe_2.9-0.tgz
Old sources: lfe archive

Reverse dependencies:

Reverse imports: gsynth, interflex, ivDiag
Reverse suggests: alpaca, broom, broom.helpers, fixest, fwildclusterboot, getspanel, insight, modelsummary, OneSampleMR, parameters, plm, sdcLog, SpatialRDD
Reverse enhances: stargazer, texreg


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