ercomp function

Estimation of the error components

This function enables the estimation of the variance components of a panel model.

ercomp(object, ...)

## S3 method for class 'plm'
ercomp(object, ...)

## S3 method for class 'pdata.frame'
ercomp(
  object,
  effect = c("individual", "time", "twoways", "nested"),
  method = NULL,
  models = NULL,
  dfcor = NULL,
  index = NULL,
  ...
)

## S3 method for class 'formula'
ercomp(
  object,
  data,
  effect = c("individual", "time", "twoways", "nested"),
  method = NULL,
  models = NULL,
  dfcor = NULL,
  index = NULL,
  ...
)

## S3 method for class 'ercomp'
print(x, digits = max(3, getOption("digits") - 3), ...)

Arguments

• object: a formula or a plm object,
• ...: further arguments.
• effect: the effects introduced in the model, see plm() for details,
• method: method of estimation for the variance components, see plm() for details,
• models: the models used to estimate the variance components (an alternative to the previous argument),
• dfcor: a numeric vector of length 2 indicating which degree of freedom should be used,
• index: the indexes,
• data: a data.frame,
• x: an ercomp object,
• digits: digits,

Returns

An object of class "ercomp": a list containing

• sigma2 a named numeric with estimates of the variance components,
• theta contains the parameter(s) used for the transformation of the variables: For a one-way model, a numeric corresponding to the selected effect (individual or time); for a two-ways model a list of length 3 with the parameters. In case of a balanced model, the numeric has length 1 while for an unbalanced model, the numerics' length equal the number of observations.

Examples

data("Produc", package = "plm")
# an example of the formula method
ercomp(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data = Produc,
       method = "walhus", effect = "time")
# same with the plm method
z <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,
         data = Produc, random.method = "walhus",
         effect = "time", model = "random")
ercomp(z)
# a two-ways model
ercomp(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data = Produc,
       method = "amemiya", effect = "twoways")

References

\insertRef AMEM:71plm

\insertRef NERLO:71plm

\insertRef SWAM:AROR:72plm

\insertRef WALL:HUSS:69plm

See Also

plm() where the estimates of the variance components are used if a random effects model is estimated

Author(s)

Yves Croissant