set.seed (12345)
m <- rnorm(20, 0, 1)
n <- 10
b1 <- 0.5
b2 <- 2
model1_b <- matrix(nrow=n, ncol=2)
model2_b <- matrix(nrow=n, ncol=2)
error <- matrix(nrow=20, ncol=n)

for (a in 1:2){
 for (b in 1:4){

   x <- (m+a)/b

   for (r in 1:10){
     repeat {

       e <- rnorm(20, 0, 0.5) # the error term
       error[,r] <- e

       # OLS estimation of Model_1
       y=b1 + b2*x + e # the true model 1
       Model_1 <- lm (y~x)
       model1_b[r,]=Model_1$coef

       # OLS estimation of Model_2
       y=b1 + b2*(x^2) + e # the true model 2
       Model_2 <- lm (y~x)
       model2_b[r,]=Model_2$coef

       if (Model_1$coef[1]!=0 & Model_2$coef[1]!=0) {break}

     } # end of repeat{} loop
    } # end of for(r){} loop
   } # end of for(b){} loop
  } # end of for(a){} loop

  error
  model1_b
  model2_b