Variance-covariance matrix of GMM or GEL

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

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

Details

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

Value

A matrix of variances and covariances

Examples


# 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)
#>               (Intercept)           ym1          ym2
#> (Intercept)  0.0030167086 -0.0002188802 -0.000686408
#> ym1         -0.0002188802  0.0019379030 -0.001486345
#> ym2         -0.0006864080 -0.0014863453  0.002234502

## GEL ##

t0 <- c(0,.5,.5)
res <- gel(g, x, t0)
vcov(res)
#>               (Intercept)           ym1           ym2
#> (Intercept)  0.0024277007 -0.0001820004 -0.0004507665
#> ym1         -0.0001820004  0.0019476920 -0.0015296322
#> ym2         -0.0004507665 -0.0015296322  0.0021093394
vcov(res, lambda = TRUE)
#>                  Lam((Intercept))       Lam(h1)       Lam(h2)       Lam(h3)
#> Lam((Intercept))     0.0000168905  1.063603e-04  1.136954e-04 -1.163313e-04
#> Lam(h1)              0.0001063603  1.173884e-03  2.276777e-04 -1.514140e-03
#> Lam(h2)              0.0001136954  2.276777e-04  1.238226e-03 -2.605773e-05
#> Lam(h3)             -0.0001163313 -1.514140e-03 -2.605773e-05  2.012997e-03
#> Lam(h4)             -0.0001328265 -6.981608e-05 -1.636578e-03 -2.737010e-04
#>                        Lam(h4)
#> Lam((Intercept)) -1.328265e-04
#> Lam(h1)          -6.981608e-05
#> Lam(h2)          -1.636578e-03
#> Lam(h3)          -2.737010e-04
#> Lam(h4)           2.210267e-03