vcovCR.ivreg: Cluster-robust variance-covariance matrix for an ivreg object.

Description

vcovCR returns a sandwich estimate of the variance-covariance matrix of a set of regression coefficient estimates from an ivreg object fitted from the AER package or the ivreg package.

Usage

# S3 method for ivreg
vcovCR(
  obj,
  cluster,
  type,
  target = NULL,
  inverse_var = FALSE,
  form = "sandwich",
  ...
)

Value

An object of class c("vcovCR","clubSandwich"), which consists of a matrix of the estimated variance of and covariances between the regression coefficient estimates.

Arguments

obj: Fitted model for which to calculate the variance-covariance matrix
cluster: Expression or vector indicating which observations belong to the same cluster. Required for ivreg objects.
type: Character string specifying which small-sample adjustment should be used, with available options "CR0", "CR1", "CR1p", "CR1S", "CR2", or "CR3". See "Details" section of vcovCR for further information.
target: Optional matrix or vector describing the working variance-covariance model used to calculate the CR2 and CR4 adjustment matrices. If a vector, the target matrix is assumed to be diagonal. If not specified, the target is taken to be an identity matrix.
inverse_var: Not used for ivreg objects.
form: Controls the form of the returned matrix. The default "sandwich" will return the sandwich variance-covariance matrix. Alternately, setting form = "meat" will return only the meat of the sandwich and setting form = B, where B is a matrix of appropriate dimension, will return the sandwich variance-covariance matrix calculated using B as the bread. form = "estfun" will return the (appropriately scaled) estimating function, the transposed crossproduct of which is equal to the sandwich variance-covariance matrix.
...: Additional arguments available for some classes of objects.

Details

For any "ivreg" objects fitted via the ivreg function from the ivreg package, only traditional 2SLS regression method (method = "OLS") is supported. clubSandwich currently cannot support robust-regression methods such as M-estimation (method = "M") or MM-estimation (method = "MM").

Examples

Run this code


if (requireNamespace("AER", quietly = TRUE)) withAutoprint({

  library(AER)
  data("CigarettesSW")
  Cigs <- within(CigarettesSW, {
    rprice <- price/cpi
    rincome <- income/population/cpi
    tdiff <- (taxs - tax)/cpi
  })

  iv_fit_AER <- AER::ivreg(log(packs) ~ log(rprice) + log(rincome) | 
                  log(rincome) + tdiff + I(tax/cpi), data = Cigs)
  vcovCR(iv_fit_AER, cluster = Cigs$state, type = "CR2")
  coef_test(iv_fit_AER, vcov = "CR2", cluster = Cigs$state)

})

pkgs_available <- 
  requireNamespace("AER", quietly = TRUE) & 
  requireNamespace("ivreg", quietly = TRUE)

if (pkgs_available) withAutoprint ({

data("CigarettesSW")
  Cigs <- within(CigarettesSW, {
    rprice <- price/cpi
    rincome <- income/population/cpi
    tdiff <- (taxs - tax)/cpi
  })
iv_fit_ivreg <- ivreg::ivreg(log(packs) ~ log(rprice) + log(rincome) | 
                  log(rincome) + tdiff + I(tax/cpi), data = Cigs)
  vcovCR(iv_fit_ivreg, cluster = Cigs$state, type = "CR2")
  coef_test(iv_fit_ivreg, vcov = "CR2", cluster = Cigs$state)
})