survey-weighted two-stage least squares for instrumental variables

svyivreg.R

library(AER)

svyivreg<-function(formula, design, ...) UseMethod("svyivreg",design)

svyivreg.survey.design<-function(formula, design){

    .data<-model.frame(design)
    .data$.weights<-weights(design,"sampling")
    model<- ivreg(formula, data=.data, weights=.weights)

    U<-estfun(model)/weights(design,"sampling")
    n<-NROW(U)
    infl<- U%*%bread(model)/n
    v<-vcov(svytotal(infl,  design))
    
    model$invinf<-model$cov.unscaled
    model$cov.unscaled<-v
    model$df.residual<-degf(design)+1-length(coef(model))
    model$sigma<-model$sigma/sqrt(mean(weights(design,"sampling")))
    model$call<-sys.call(-1)
    class(model)<-"svyivreg"
    model
}

print.svyivreg<-AER:::print.ivreg

summary.svyivreg<-function(object, df = NULL, ...){
    AER:::summary.ivreg(object, vcov.=NULL, df=df, diagnostics=FALSE,...)
}

vcov.svyivreg<-function(object,...) object$cov.unscaled

svyivreg.svyrep.design<-function(formula, design,return.replicates=FALSE,...){

    withReplicates(design, return.replicates=return.replicates,
                   function(.weights, .data){
                       .data$.pweights<-.weights
                       m<-ivreg(formula,data= .data, weights=.pweights)
                       coef(m)
                   })
                      
                      
    }