row-wise iteration in a dataframe where each row depends on previous values

tidyverse
,
2

I would use purrr::accumulate in this case of a lag of one. It just require a small modification in your function to take two arguments : previous value and actual value.
See

library(dplyr)
#> 
#> Attachement du package : 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(purrr)

x <- tibble(a = c(1:10),
            b = c(seq(100, 140, 10), rep(NA_real_, 5)) )

fill_in <- function(prev, new, growth = 0.03) {
  if_else(!is.na(new), new, prev * (1 + growth))
}

options(pillar.sigfig = 5)
x %>%
  mutate(b = accumulate(b, fill_in))
#> # A tibble: 10 x 2
#>        a      b
#>    <int>  <dbl>
#>  1     1 100   
#>  2     2 110   
#>  3     3 120   
#>  4     4 130   
#>  5     5 140   
#>  6     6 144.2 
#>  7     7 148.53
#>  8     8 152.98
#>  9     9 157.57
#> 10    10 162.30

Created on 2019-08-31 by the reprex package (v0.3.0)

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