Linear panel data models in R: The PLM package

November 10, 2007

(This article was first published on Dataninja » R, and kindly contributed to R-bloggers)

The plm package for R lets you run a number of common panel data models, including

  • The fixed effects (or within) estimator
  • The random effects GLS estimator

It also allows for general GLS estimation, as well as GMM estimation, and includes a feature for heteroscedasticity consistent covariance estimation.

It’s very easy to use, it simply requires that you use a special type of dataframe that specifies which variable is the individual and which variable is the cluster/group (this is done using the pdata.frame) command. Once this is done, you can estimate models using the plm command and its options.

See the documentation (PDF) for more.

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