plm
Package - Linear Models and Tests for Panel Dataplm
is a package for panel data econometrics for the R statistical computing
environment. The package includes functions for model estimation, testing, robust
covariance matrix estimation, panel data manipulation and information. It was
first published on CRAN in 2006.
Be sure to read the NEWS on CRAN for any changes in new releases (new features, bugfixes, other improvements, ...).
Non-exhaustive function overview:
plm
: panel data estimators (within/fixed effects, random effects, between,
first-difference, nested random effects), incl. instrumental-variable
estimation techniques (IV) and Hausman-Taylor-style models,pgmm
: generalized method of moments (GMM) estimation for panel data,pggls
: estimation of general feasible generalized least squares models,pmg
: mean groups (MG), demeaned MG and common correlated effects (CCEMG) estimators,pcce
: estimators for common correlated effects mean groups (CCEMG) and pooled (CCEP) for panel data with common factors,pvcm
: variable coefficients models,pldv
: panel estimators for limited dependent variables.
Testing functions:
phtest
, pFtest
, pooltest
, plmtest
, pwaldtest
, piest
, aneweytest
, mtest
, sargan
),pbgtest
, pwfdtest
, pbnftest
, pdwtest
, pwartest
, pbsytest
, pbltest
), pcdtest
),purtest
, cipstest
, phansitest
),panel Granger (non-)causality (pgrangertest
).
Robust covariance matrix estimators (incl. various weighting schemes for small sample adjustment):
vcovHC
: Arellano (1987), White (1980),vcovBK
: Beck and Katz (1995) (PCSE),vcovNW
: Newey and West (1987),vcovDC
: double-clustering robust (Thompson (2011), Cameron et al. (2011)),vcovSCC
: Driscoll and Kraay (1998).
An enhanced data frame, called pdata.frame
, to deal with data sets for which
observations are identified by a combination of two indexes.
Panel data transformation functions (e.g., Within
, Between
, between
, lag
,
lead
, diff
).
Other functions relating to panel data sets, e.g.:
pdim
), is.pbalanced
) and consecutiveness (regularity) (is.pconsecutive
)
as well as functions to change data to conform to these properties
(make.pbalanced
, make.pconsecutive
),punbalancedness
) (Ahrens/Pincus (1981)).To install the released version from CRAN:
install.packages("plm")
The package's CRAN website is https://cran.r-project.org/package=plm.
The development of package plm
takes place on GitHub at https://github.com/ycroissant/plm.
To install the development version from GitHub, use, e.g.:
# install.packages("remotes") # remove '#' if pkg 'remotes' is not installed
remotes::install_github("ycroissant/plm")
Package plm comes with documentation: Besides the usual help pages for each function,
the vignettes provide a gentle introduction to the package and some functions.
Vignettes are available at the package's CRAN website https://cran.r-project.org/package=plm
and can be browsed from within R by browseVignettes("plm")
.
New package users are advised to start with the first vignette Panel data econometrics in R: the plm package for an overview of the package. A more in-depth treatment of estimation of error component models and instrument variable models is in the second vignette Estimation of error component models with the plm function.
Further, many textbooks treat package plm
and/or use it in their examples:
Croissant/Millo, Panel Data Econometrics with R, 2019, John Wiley & Sons, Hoboken.
Kleiber/Zeileis, Applied Econometrics with R, 2008, Springer, New York. Esp. chapter 3.6.
Hanck/Arnold/Gerber/Schmelzer, Econometrics with R, online book https://www.econometrics-with-r.org/. Esp. chapter 10.
Heiss, Using R for Introductory Econometrics, 2nd edition, 2020, Independent Publishing, DÃ¼sseldorf, also available online at http://www.urfie.net/. A companion book using R to Wooldridge, Introductory Econometrics, esp. chapters 13-14.
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.