R bootstrap regression non-numeric argument

Question

I want to do a bootstrap prediction of the future values of my two time series pibusa and popfra from my dataset expli.bv, using a VAR model with a lag p = 2. I can't seem to make it work as I get non numeric variables at each replication... Here is my code :

 library(vars)
 p <- 2
 Model_expli <- VAR(expli.bv, p = p, type = "const", season = NULL, exogen = NULL)

 m <- 1000  # Number of bootstrap replications
 n <- nrow(expli.bv)  # Number of observations in my dataset

 nvybb <- matrix(0, m, p)
 zb <- matrix(0, m, p)

for (b in 1:m) {
   indboot <- sample(1:n, n, replace = TRUE)
   ub <- Model_expli$residuals[indboot, , drop = FALSE]

   # Prediction bootstrap of Y (future)
   yb <- predict(Model_expli, n.ahead = p, ci = 0.95, dumvar = NULL, dumvar.forecast = 
 NULL, dumvar.match = FALSE, lag.max = NULL, nahead = NULL, 
                 ci.method = "ET", ortho = FALSE, VAR.extra = NULL, dumvar.include = 
 TRUE)

   # Construction of Z*(i)
   for (i in 1:p) {
     yb_values <- as.vector(yb[[i]])
     fitted_values <- as.vector(Model_expli$fitted.values[, i])

     if (all(is.numeric(yb_values)) && all(is.numeric(fitted_values))) {
       z <- (yb_values - fitted_values) / sqrt(diag(var(ub[, i])))
       nvybb[b, i] <- yb_values
       zb[b, i] <- z
     } else {
  # case when variable is non numeric
       cat("Variable non numérique détectée dans la réplication", b, "de la variable", 
 i, "\n")
     }
   }
 }

And here is the head of my dataset for reproducibility :

  structure(c(1023.984, 1059.458, 1101.609, 1140.716, 1158.725, 
  1171.112, 218035000, 220239000, 222585000, 225055000, 227225000, 
  229466000), dim = c(6L, 2L), dimnames = list(NULL, structure(c("pibfra", 
  "popusa"), dim = 1:2)), tsp = c(1976, 1981, 1), class = c("mts", 
  "ts", "matrix", "array"))

Can anyone help me ?