Repository files navigation

plm is a package for panel data econometrics for theR statistical computingenvironment. The package includes functions for model estimation, testing, robustcovariance matrix estimation, panel data manipulation and information. It wasfirst published onCRAN in 2006.

Be sure to read the NEWS onCRAN (orin thedevelopment repository)for any changes in new releases (new features, bugfixes, other improvements, ...).

Non-exhaustive function overview:

• Functions to estimate models:

  • plm: panel data estimators (within/fixed effects, random effects, between,first-difference, nested random effects), incl. instrumental-variableestimation 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:

  • model specification (phtest,pFtest,pooltest,plmtest,pwaldtest,piest,aneweytest,mtest,sargan),
  • serial correlation (pbgtest,pwfdtest,pbnftest,pdwtest,pwartest,pbsytest,pbltest),
  • cross-sectional dependence (pcdtest),
  • panel unit root (purtest,cipstest,phansitest),
  • panel Granger (non-)causality (pgrangertest).

• Robust covariance matrix estimators (incl. various weighting schemesfor 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, calledpdata.frame, to deal with data sets for whichobservations 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.:

  • checks for panel data dimensions (individual, time, group) and balancedness (pdim),
  • checks for panel balancedness (is.pbalanced) and consecutiveness (regularity) (is.pconsecutive)as well as functions to change data to conform to these properties(make.pbalanced,make.pconsecutive),
  • measures for unbalancedness of data (punbalancedness) (Ahrens/Pincus (1981)).

To install the released version fromCRAN:

install.packages("plm")

The package's CRAN website ishttps://cran.r-project.org/package=plm.

The development of packageplm takes place on GitHub athttps://github.com/ycroissant/plm.To install the development version fromGitHub, use, e.g.:

# install.packages("remotes") # remove '#' if pkg 'remotes' is not installedremotes::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 websitehttps://cran.r-project.org/package=plmand can be browsed from within R bybrowseVignettes("plm").

New package users are advised to start with the first vignettePanel 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 instrumentvariable models is in the second vignetteEstimation of error component modelswith the plm function.

Further, many textbooks treat packageplm 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 bookhttps://www.econometrics-with-r.org/. Esp. chapter 10.

• Heiss,Using R for Introductory Econometrics, 2nd edition, 2020,Independent Publishing, Düsseldorf, also available online athttp://www.urfie.net/.A companion book using R to Wooldridge,Introductory Econometrics, esp.chapters 13-14.