plmtest  R Documentation 
Test of individual and/or time effects for panel models.
plmtest(x, ...)
## S3 method for class 'plm'
plmtest(
x,
effect = c("individual", "time", "twoways"),
type = c("honda", "bp", "ghm", "kw"),
...
)
## S3 method for class 'formula'
plmtest(
x,
data,
...,
effect = c("individual", "time", "twoways"),
type = c("honda", "bp", "ghm", "kw")
)
x 
an object of class 
... 
further arguments passed to 
effect 
a character string indicating which effects are
tested: individual effects ( 
type 
a character string indicating the test to be performed:

data 
a 
These Lagrange multiplier tests use only the residuals of the
pooling model. The first argument of this function may be either a
pooling model of class plm
or an object of class formula
describing the model. For input within (fixed effects) or random
effects models, the corresponding pooling model is calculated
internally first as the tests are based on the residuals of the
pooling model.
The "bp"
test for unbalanced panels was derived in
\insertCiteBALT:LI:90;textualplm
(1990), the "kw"
test for unbalanced panels in
\insertCiteBALT:CHAN:LI:98;textualplm.
The "ghm"
test and the "kw"
test were extended to twoway
effects in \insertCiteBALT:CHAN:LI:92;textualplm.
For a concise overview of all these statistics see \insertCiteBALT:03;textualplm, Sec. 4.2, pp. 68–76 (for balanced panels) and Sec. 9.5, pp. 200–203 (for unbalanced panels).
An object of class "htest"
.
For the KingWu statistics ("kw"
), the oneway statistics
("individual"
and "time"
) coincide with the respective
Honda statistics ("honda"
); twoway statistics of "kw"
and
"honda"
differ.
Yves Croissant (initial implementation), Kevin Tappe (generalization to unbalanced panels)
BALT:13plm
\insertRefBALT:LI:90plm
\insertRefBALT:CHAN:LI:92plm
\insertRefBALT:CHAN:LI:98plm
\insertRefBREU:PAGA:80plm
\insertRefGOUR:HOLL:MONF:82plm
\insertRefHOND:85plm
\insertRefKING:WU:97plm
pFtest()
for individual and/or time effects tests based
on the within model.
data("Grunfeld", package = "plm")
g < plm(inv ~ value + capital, data = Grunfeld, model = "pooling")
plmtest(g)
plmtest(g, effect="time")
plmtest(inv ~ value + capital, data = Grunfeld, type = "honda")
plmtest(inv ~ value + capital, data = Grunfeld, type = "bp")
plmtest(inv ~ value + capital, data = Grunfeld, type = "bp", effect = "twoways")
plmtest(inv ~ value + capital, data = Grunfeld, type = "ghm", effect = "twoways")
plmtest(inv ~ value + capital, data = Grunfeld, type = "kw", effect = "twoways")
Grunfeld_unbal < Grunfeld[1:(nrow(Grunfeld)1), ] # create an unbalanced panel data set
g_unbal < plm(inv ~ value + capital, data = Grunfeld_unbal, model = "pooling")
plmtest(g_unbal) # unbalanced version of test is indicated in output
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