vcovG {plm}

Generic Lego building block for Robust Covariance Matrix Estimators

Description

Generic Lego building block for robust covariance matrix estimators of the vcovXX kind for panel models.

Usage

vcovG(x, ...)

## S3 method for class 'plm'
vcovG(
  x,
  type = c("HC0", "sss", "HC1", "HC2", "HC3", "HC4"),
  cluster = c("group", "time"),
  l = 0,
  inner = c("cluster", "white", "diagavg"),
  ...
)

## S3 method for class 'pcce'
vcovG(
  x,
  type = c("HC0", "sss", "HC1", "HC2", "HC3", "HC4"),
  cluster = c("group", "time"),
  l = 0,
  inner = c("cluster", "white", "diagavg"),
  ...
)

Arguments

x

an object of class "plm" or "pcce"

...

further arguments

type

the weighting scheme used, one of "HC0", "sss", "HC1", "HC2", "HC3", "HC4",

cluster

one of "group", "time",

l

lagging order, defaulting to zero

inner

the function to be applied to the residuals inside the sandwich: one of "cluster" or "white" or "diagavg",

Details

vcovG is the generic building block for use by higher–level wrappers vcovHC(), vcovSCC(), vcovDC(), and vcovNW(). The main use of vcovG is to be used internally by the former, but it is made available in the user space for use in non–standard combinations. For more documentation, see see wrapper functions mentioned.

Value

An object of class "matrix" containing the estimate of the covariance matrix of coefficients.

Author(s)

Giovanni Millo

References

Millo G (2017). “Robust standard error estimators for panel models: A unifying approach.” Journal of Statistical Software, 82(3), 1–27.

See Also

vcovHC(), vcovSCC(), vcovDC(), vcovNW(), and vcovBK() albeit the latter does not make use of vcovG.

Examples

data("Produc", package="plm")
zz <- plm(log(gsp)~log(pcap)+log(pc)+log(emp)+unemp, data=Produc,
model="pooling")
## reproduce Arellano's covariance matrix
vcovG(zz, cluster="group", inner="cluster", l=0)
## define custom covariance function
## (in this example, same as vcovHC)
myvcov <- function(x) vcovG(x, cluster="group", inner="cluster", l=0)
summary(zz, vcov = myvcov)
## use in coefficient significance test
library(lmtest)
## robust significance test
coeftest(zz, vcov. = myvcov)