plm (version 2.6-4)

plmtest: Lagrange FF Multiplier Tests for Panel Models

Description

Test of individual and/or time effects for panel models.

Usage

plmtest(x, ...)
# S3 method for plm
plmtest(
  x,
  effect = c("individual", "time", "twoways"),
  type = c("honda", "bp", "ghm", "kw"),
  ...
)
# S3 method for formula
plmtest(
  x,
  data,
  ...,
  effect = c("individual", "time", "twoways"),
  type = c("honda", "bp", "ghm", "kw")
)

Value

An object of class "htest".

Arguments

x

an object of class "plm" or a formula of class "formula",

...

further arguments passed to plmtest.

effect

a character string indicating which effects are tested: individual effects ("individual"), time effects ("time") or both ("twoways"),

type

a character string indicating the test to be performed:

• "honda" (default) for HOND:85;textualplm,

• "bp" for BREU:PAGA:80;textualplm,

• "kw" for KING:WU:97;textualplm, or

• "ghm" for GOUR:HOLL:MONF:82;textualplm for unbalanced panel data sets, the respective unbalanced version of the tests are computed,

data

a data.frame,

Author

Yves Croissant (initial implementation), Kevin Tappe (generalization to unbalanced panels)

Details

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 BALT:LI:90;textualplm (1990), the "kw" test for unbalanced panels in BALT:CHAN:LI:98;textualplm.

The "ghm" test and the "kw" test were extended to two-way effects in BALT:CHAN:LI:92;textualplm.

For a concise overview of all these statistics see BALT:03;textualplm, Sec. 4.2, pp. 68--76 (for balanced panels) and Sec. 9.5, pp. 200--203 (for unbalanced panels).

References

BALT:13plm

BALT:LI:90plm

BALT:CHAN:LI:92plm

BALT:CHAN:LI:98plm

BREU:PAGA:80plm

GOUR:HOLL:MONF:82plm

HOND:85plm

KING:WU:97plm

See Also

pFtest() for individual and/or time effects tests based on the within model.

Examples

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