plmtest: Lagrange FF Multiplier Tests for Panel Models

In ycroissant/plm: Linear Models for Panel Data

Lagrange FF Multiplier Tests for Panel Models

Description

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

Usage

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")
)

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 \insertCiteHOND:85;textualplm, "bp" for \insertCiteBREU:PAGA:80;textualplm, "kw" for \insertCiteKING:WU:97;textualplm, or "ghm" for \insertCiteGOUR:HOLL:MONF:82;textualplm for unbalanced panel data sets, the respective unbalanced version of the tests are computed,
data	a data.frame,

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 \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 two-way 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).

Value

An object of class "htest".

Note

For the King-Wu statistics ("kw"), the oneway statistics ("individual" and "time") coincide with the respective Honda statistics ("honda"); twoway statistics of "kw" and "honda" differ.

Author(s)

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

References

\insertRef

BALT:13plm

\insertRef

BALT:LI:90plm

\insertRef

BALT:CHAN:LI:92plm

\insertRef

BALT:CHAN:LI:98plm

\insertRef

BREU:PAGA:80plm

\insertRef

GOUR:HOLL:MONF:82plm

\insertRef

HOND:85plm

\insertRef

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

ycroissant/plm documentation built on July 8, 2024, 3:59 a.m.