A I am trying to fill a table through a loop loop, but it is taking too long. How can I improve loop performance?

Question

the columns and table values will be filled in as the cycle runs. Briefly, I have a table with customer data (BD) and another table with expected future values by age (ESP). And what the cycle does is, for an x-age client, go get all the expected values for the current age and future age that are in another table. In excel could do this quickly. How to improve cycle performance in R?

ESP table and BD table:

ESP
# A tibble: 10 x 2
   IDADE    ESP
   <dbl>  <dbl>
 1     0 100000
 2     1  99129
 3     2  99057
 4     3  99010
 5     4  98977
 6     5  98948
 7     6  98921
 8     7  98897
 9     8  98876
10     9  98855

BD
   IDADE_ACT
1         84
2         44
3         24
4         23
5         23
6         22
7         25
8         22
9         22
10        22

the R CODE I’m using

FUN <- function (BD, ESP) {
  anos<-ncol(ESP)
  n <- nrow(BD)
  DF <-  data.frame()
  for (i in 1:n) {
    idade <- BD[i, ]$IDADE_ACT
    if (is.na(idade)) {DF[i, ] <- 0}
    else {
      j <- 1
      while (j <= anos + 1) {
        if (idade >= 0 && idade + j <= nrow(ESP)) {
          DF[i, j] <- ESP[idade + j, 2]
        } else{(DF[i, j] <- 0)}
        j <- j + 1
      }
    } 
  }
  colnames(DF) <- c(0:anos)
  return(DF)
}