library(dplyr)
library(dtplyr)
library(magrittr)
library(data.table)
library(taxstats)
library(grattan)

MYEFO <-
  data.table(fy_year = yr2fy(2017:2020),
             r = c(0.023, 0.025, 0.033, 0.035))

Pessimistic <-
  data.table(fy_year = yr2fy(2017:2020),
             r = c(0.021, 0.021, 0.031, 0.031))

tax_by_scenario <- function(FY, assumption = c("MYEFO", "Pessimistic")){
  h <- as.integer(fy2yr(FY) - 2013L)
  assumption <- match.arg(assumption)
  if (assumption == "MYEFO"){
    sample_file_MYEFO <-
      sample_file_1213 %>%
      copy %>%
      project(fy.year.of.sample.file = "2012-13", h = h, wage.series = MYEFO)

    tax_collected <-
      sample_file_MYEFO %$%
      sum(income_tax(Taxable_Income,
                     fy.year = "2016-17",
                     .dots.ATO = copy(sample_file_MYEFO)) * WEIGHT) / 1e9
  } else {
    sample_file_Pessimistic <-
      sample_file_1213 %>%
      copy %>%
      project(fy.year.of.sample.file = "2012-13", h = h, wage.series = Pessimistic)

    tax_collected <-
      sample_file_Pessimistic %$%
      sum(income_tax(Taxable_Income,
                     fy.year = "2016-17",
                     .dots.ATO = copy(sample_file_Pessimistic)) * WEIGHT) / 1e9
  }
  return(tax_collected)
}

Answer <-
  CJ(FY = yr2fy(2017:2020), Assumption = c("MYEFO", "Pessimistic")) %>%
  as.data.frame %>%
  rowwise %>%
  mutate(tax = tax_by_scenario(FY, Assumption))

Answer %>%
  fwrite("~/outbox/Tax-collected-billions-by-fy-year-and-assumptions.csv")