pbgtest | R Documentation |
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"),
...
)
x |
an object of class |
... |
further arguments (see |
order |
an integer indicating the order of serial correlation
to be tested for. |
type |
type of test statistic to be calculated; either
|
data |
only relevant for formula interface: data set for which
the respective panel model (see |
model |
only relevant for formula interface: compute test
statistic for model |
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 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 \insertCiteWOOL: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.
An object of class "htest"
.
The argument order
defaults to the minimum number of
observations over the time dimension, while for
lmtest::bgtest
it defaults to 1
.
Giovanni Millo
BREU:78plm
\insertRefGODF:78plm
\insertRefWOOL:02plm
\insertRefWOOL:10plm
\insertRefWOOL:13plm Sec. 12.2, pp. 421–422.
For the original test in package 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.
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")
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