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

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",
  ...
)

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.

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.

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").

See also

vcovCR

Examples

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)

})
#> > library(AER)
#> Loading required package: car
#> Loading required package: carData
#> 
#> Attaching package: ‘car’
#> The following object is masked from ‘package:metafor’:
#> 
#>     vif
#> Loading required package: lmtest
#> Loading required package: zoo
#> 
#> Attaching package: ‘zoo’
#> The following objects are masked from ‘package:base’:
#> 
#>     as.Date, as.Date.numeric
#> Loading required package: sandwich
#> Loading required package: survival
#> > 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$state, type = "CR2")
#>              (Intercept) log(rprice) log(rincome)
#> (Intercept)   0.31782384 -0.08285646   0.02774789
#> log(rprice)  -0.08285646  0.03453204  -0.03009923
#> log(rincome)  0.02774789 -0.03009923   0.04292233
#> > coef_test(iv_fit_AER, vcov = "CR2", cluster = Cigs$state)
#>         Coef. Estimate    SE t-stat d.f. (Satt) p-val (Satt) Sig.
#>   (Intercept)    9.736 0.564  17.27        22.0       <0.001  ***
#>   log(rprice)   -1.229 0.186  -6.61        21.1       <0.001  ***
#>  log(rincome)    0.257 0.207   1.24        23.5        0.227     

pkgs_available <- 
  requireNamespace("AER", quietly = TRUE) & 
  requireNamespace("ivreg", quietly = TRUE)
#> Registered S3 methods overwritten by 'ivreg':
#>   method              from
#>   anova.ivreg         AER 
#>   hatvalues.ivreg     AER 
#>   model.matrix.ivreg  AER 
#>   predict.ivreg       AER 
#>   print.ivreg         AER 
#>   print.summary.ivreg AER 
#>   summary.ivreg       AER 
#>   terms.ivreg         AER 
#>   update.ivreg        AER 
#>   vcov.ivreg          AER 

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)
})
#> > 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$state, type = "CR2")
#>              (Intercept) log(rprice) log(rincome)
#> (Intercept)   0.31782384 -0.08285646   0.02774789
#> log(rprice)  -0.08285646  0.03453204  -0.03009923
#> log(rincome)  0.02774789 -0.03009923   0.04292233
#> > coef_test(iv_fit_ivreg, vcov = "CR2", cluster = Cigs$state)
#>         Coef. Estimate    SE t-stat d.f. (Satt) p-val (Satt) Sig.
#>   (Intercept)    9.736 0.564  17.27        22.0       <0.001  ***
#>   log(rprice)   -1.229 0.186  -6.61        21.1       <0.001  ***
#>  log(rincome)    0.257 0.207   1.24        23.5        0.227