F Test for Individual and/or Time Effects

Test of individual and/or time effects based on the comparison of the within and the pooling model.

pFtest(x, ...)

# S3 method for class 'formula'
pFtest(x, data, ...)

# S3 method for class 'plm'
pFtest(x, z, ...)

Arguments

x

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

...

further arguments.

data

a data.frame,

z

an object of class "plm",

Value

An object of class "htest".

Details

For the plm method, the argument of this function is two plm objects, the first being a within model, the second a pooling model. The effects tested are either individual, time or twoways, depending on the effects introduced in the within model.

See also

plmtest() for Lagrange multiplier tests of individuals and/or time effects.

Author

Yves Croissant

Examples

data("Grunfeld", package="plm")
gp <- plm(inv ~ value + capital, data = Grunfeld, model = "pooling")
gi <- plm(inv ~ value + capital, data = Grunfeld,
          effect = "individual", model = "within")
gt <- plm(inv ~ value + capital, data = Grunfeld,
          effect = "time", model = "within")
gd <- plm(inv ~ value + capital, data = Grunfeld,
          effect = "twoways", model = "within")
pFtest(gi, gp)
#> 
#> 	F test for individual effects
#> 
#> data:  inv ~ value + capital
#> F = 49.177, df1 = 9, df2 = 188, p-value < 2.2e-16
#> alternative hypothesis: significant effects
#> 
pFtest(gt, gp)
#> 
#> 	F test for time effects
#> 
#> data:  inv ~ value + capital
#> F = 0.23451, df1 = 19, df2 = 178, p-value = 0.9997
#> alternative hypothesis: significant effects
#> 
pFtest(gd, gp)
#> 
#> 	F test for twoways effects
#> 
#> data:  inv ~ value + capital
#> F = 17.403, df1 = 28, df2 = 169, p-value < 2.2e-16
#> alternative hypothesis: significant effects
#> 
pFtest(inv ~ value + capital, data = Grunfeld, effect = "twoways")
#> 
#> 	F test for twoways effects
#> 
#> data:  inv ~ value + capital
#> F = 17.403, df1 = 28, df2 = 169, p-value < 2.2e-16
#> alternative hypothesis: significant effects
#>