R/etreg2steprobVcov.R

In ssmrob: Robust Estimation and Inference in Sample Selection Models

etreg2steprobVcov <-
function(y1vec, y2vec, x1Matr, x2Matr, eststage1, eststage2, eststage2sigma, weights = rep(1,nrow(y1vec)), t.c = 1.345)
{
  N <- length(y1vec)
  sumheck <- 0 #
  for(i in 1:N)  # sandwich estimator of the first term
  {
    sumheck <- sumheck + PsiMest(x2Matr[i,], y2vec[i], eststage2, eststage2sigma, t.c, weights[i])%*%
                                t(PsiMest(x2Matr[i,], y2vec[i], eststage2, eststage2sigma, t.c, weights[i]))
  }
  
  s1 <- matrix(0, length(eststage2) - 1, length(eststage1$coeff))
  s2 <- 0   
  for(i in 1:N)
  {
    if((y2vec[i] - t(x2Matr[i,]) %*% as.vector(eststage2)) / eststage2sigma < (-t.c))
    {
      s1 <- s1 + 0
      s2 <- s2 - t.c*weights[i]*drop((y1vec[i])*dLambdadSM(x1Matr[i,],eststage1$coeff) - 
                                  (1-y1vec[i])*dLambdadSM5(x1Matr[i,],eststage1$coeff))*(x1Matr[i,])
    }
    else if(((y2vec[i] - t(x2Matr[i,]) %*% as.vector(eststage2))) / eststage2sigma > (t.c))
    {
      s1=s1 + 0
      s2=s2 + t.c*weights[i]*drop((y1vec[i])*dLambdadSM(x1Matr[i,],eststage1$coeff) - 
                                  (1-y1vec[i])*dLambdadSM5(x1Matr[i,],eststage1$coeff))*(x1Matr[i,])
    }
    else {
      s1=s1+( x2Matr[i,1:dim(x2Matr)[2]-1] )%*%t(x1Matr[i,])*eststage2[dim(x2Matr)[2]]*weights[i]*drop((y1vec[i])*dLambdadSM(x1Matr[i,],eststage1$coeff) - (1-y1vec[i])*dLambdadSM5(x1Matr[i,],eststage1$coeff))/eststage2sigma
      s2=s2+(x2Matr[i,dim(x2Matr)[2]]*eststage2[dim(x2Matr)[2]])*weights[i]*((y1vec[i])*c(dLambdadSM(x1Matr[i,], eststage1$coeff)) - (1-y1vec[i])*c(dLambdadSM5(x1Matr[i,],eststage1$coeff)))/eststage2sigma*x1Matr[i,]
    }
  }
  xdx <- rbind(s1,s2)
  term2 <- xdx%*%vcov(eststage1)%*%t(xdx)  
  M2inv <- solve(MmatrM(x2Matr,y2vec,eststage2,eststage2sigma,t.c,weights))
  result <- M2inv%*%(sumheck+term2)%*%M2inv   # asymptotic variance 
  return(result)
}