Test of Poolability

A Chow test for the poolability of the data.

pooltest(x, ...)

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

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

Arguments

x

an object of class "plm" for the plm method; an object of class "formula" for the formula interface,

...

further arguments passed to plm.

z

an object of class "pvcm" obtained with model="within",

data

a data.frame,

Value

An object of class "htest".

Details

pooltest is a F test of stability (or Chow test) for the coefficients of a panel model. For argument x, the estimated plm object should be a "pooling" model or a "within" model (the default); intercepts are assumed to be identical in the first case and different in the second case.

Author

Yves Croissant

Examples

data("Gasoline", package = "plm")
form <- lgaspcar ~ lincomep + lrpmg + lcarpcap
gasw <- plm(form, data = Gasoline, model = "within")
gasp <- plm(form, data = Gasoline, model = "pooling")
gasnp <- pvcm(form, data = Gasoline, model = "within")
pooltest(gasw, gasnp)
#> 
#> 	F statistic
#> 
#> data:  form
#> F = 27.335, df1 = 51, df2 = 270, p-value < 2.2e-16
#> alternative hypothesis: unstability
#> 
pooltest(gasp, gasnp)
#> 
#> 	F statistic
#> 
#> data:  form
#> F = 129.32, df1 = 68, df2 = 270, p-value < 2.2e-16
#> alternative hypothesis: unstability
#> 

pooltest(form, data = Gasoline, effect = "individual", model = "within")
#> 
#> 	F statistic
#> 
#> data:  form
#> F = 27.335, df1 = 51, df2 = 270, p-value < 2.2e-16
#> alternative hypothesis: unstability
#> 
pooltest(form, data = Gasoline, effect = "individual", model = "pooling")
#> 
#> 	F statistic
#> 
#> data:  form
#> F = 129.32, df1 = 68, df2 = 270, p-value < 2.2e-16
#> alternative hypothesis: unstability
#>