Why are tha standard error of my coefficients the same?

Question

I am trying to run a simulation code, And in the matrix named par.est1 I am saving in the 5th and 6th columns the standard errors of the coefficients b1 and b2, but those happen to be the exact same on the 1000 repetitions. Could anyone know why is this happening? Maybe it has something to do with the way that I created the correlated variables?

This is the code:

set.seed(185736)
reps <- 1000 #repetitions
par.est1 <- matrix(NA, nrow=reps, ncol=6) 
b1 <- 4
b2 <- 5.8
n <- 26 
r <- 0.1

#Create correlated variables
library(MASS)
data <- mvrnorm(n=n, mu=c(0, 0), Sigma=matrix(c(1, r, r, 1), nrow=2), empirical=TRUE)

V1 = data[, 1]  # standard normal (mu=0, sd=1)
V2 = data[, 2]  

cor(V1, V2)  

for(i in 1:reps){
  Y <- V1*b1+V2*b2+rnorm(n,0,1) #The true DGP, with N(0,1) error
  model1 <- lm(Y~V1+V2) 
  vcv1 <- vcov(model1)

  par.est1[i,1] <- model1$coef[1] 
  par.est1[i,2] <- model1$coef[2] 
  par.est1[i,3] <- model1$coef[3]

  par.est1[i,4] <- sqrt(diag(vcv1)[1]) #SE 
  par.est1[i,5] <- sqrt(diag(vcv1)[2])
  par.est1[i,6] <- sqrt(diag(vcv1)[3])
}

Thank you.

Thanks user2554330.

Any way I can make correlated variables with different means and variances??