pbgtest function

Breusch--Godfrey Test for Panel Models

Test of serial correlation for (the idiosyncratic component of) the errors in panel models.

pbgtest(x, ...)

## S3 method for class 'panelmodel'
pbgtest(x, order = NULL, type = c("Chisq", "F"), ...)

## S3 method for class 'formula'
pbgtest(
  x,
  order = NULL,
  type = c("Chisq", "F"),
  data,
  model = c("pooling", "random", "within"),
  ...
)

Arguments

• x: an object of class "panelmodel" or of class "formula",

• ...: further arguments (see lmtest::bgtest()).

• order: an integer indicating the order of serial correlation to be tested for. NULL (default) uses the minimum number of observations over the time dimension (see also section Details below),

• type: type of test statistic to be calculated; either "Chisq" (default) for the Chi-squared test statistic or "F"

  for the F test statistic,

• data: only relevant for formula interface: data set for which the respective panel model (see model) is to be evaluated,

• model: only relevant for formula interface: compute test statistic for model pooling (default), random, or within. When model is used, the data argument needs to be passed as well,

Returns

An object of class "htest".

Details

This Lagrange multiplier test uses the auxiliary model on (quasi-)demeaned data taken from a model of class plm which may be a pooling (default for formula interface), random or within model. It performs a Breusch--Godfrey test (using bgtest

from package list("lmtest") on the residuals of the (quasi-)demeaned model, which should be serially uncorrelated under the null of no serial correlation in idiosyncratic errors, as illustrated in \insertCite WOOL:10;textualplm. The function takes the demeaned data, estimates the model and calls bgtest.

Unlike most other tests for serial correlation in panels, this one allows to choose the order of correlation to test for.

Note

The argument order defaults to the minimum number of observations over the time dimension, while for lmtest::bgtest it defaults to 1.

Examples

data("Grunfeld", package = "plm")
g <- plm(inv ~ value + capital, data = Grunfeld, model = "random")

# panelmodel interface
pbgtest(g)
pbgtest(g, order = 4)

# formula interface
pbgtest(inv ~ value + capital, data = Grunfeld, model = "random")

# F test statistic (instead of default type="Chisq")
pbgtest(g, type="F")
pbgtest(inv ~ value + capital, data = Grunfeld, model = "random", type = "F")

References

\insertRef BREU:78plm

\insertRef GODF:78plm

\insertRef WOOL:02plm

\insertRef WOOL:10plm

\insertRef WOOL:13plm

Sec. 12.2, pp. 421--422.

See Also

For the original test in package list("lmtest") see lmtest::bgtest(). See pdwtest() for the analogous panel Durbin--Watson test. See pbltest(), pbsytest(), pwartest() and pwfdtest() for other serial correlation tests for panel models.

Author(s)

Giovanni Millo