gmm (version 1.6-2)

vcov: Variance-covariance matrix of GMM or GEL

Description

It extracts the matrix of variances and covariances from gmm or gel objects.

Usage

# S3 method for gmm
vcov(object, ...)
# S3 method for gel
vcov(object, lambda = FALSE, ...)
# S3 method for tsls
vcov(object, type=c("Classical","HC0","HC1","HAC"),
                    hacProp = list(), ...)
# S3 method for ategel
vcov(object, lambda = FALSE, robToMiss = TRUE, ...)

Arguments

object

An object of class gmm or gmm returned by the function gmm or gel

lambda

If set to TRUE, the covariance matrix of the Lagrange multipliers is produced.

type

Type of covariance matrix for the meat

hacProp

A list of arguments to pass to kernHAC

robToMiss

If TRUE, it computes the robust to misspecification covariance matrix

...

Other arguments when vcov is applied to another class object

Value

A matrix of variances and covariances

Details

For tsls(), if vcov is set to a different value thand "Classical", a sandwich covariance matrix is computed.

Examples

# NOT RUN {
# GMM #
n = 500
phi<-c(.2,.7)
thet <- 0
sd <- .2
x <- matrix(arima.sim(n = n,list(order = c(2,0,1), ar = phi, ma = thet, sd = sd)), ncol = 1)
y <- x[7:n]
ym1 <- x[6:(n-1)]
ym2 <- x[5:(n-2)]

H <- cbind(x[4:(n-3)], x[3:(n-4)], x[2:(n-5)], x[1:(n-6)])
g <- y ~ ym1 + ym2
x <- H

res <- gmm(g, x)
vcov(res)

## GEL ##

t0 <- c(0,.5,.5)
res <- gel(g, x, t0)
vcov(res)
vcov(res, lambda = TRUE)

# }