data-raw/children.R

In jjchern/melig: Trends in Medicaid Income Eligibility Limits

# Medicaid and CHIP income cutoff for children --------------------------------

library(tidyverse)

read_csv("data-raw/infants_age_0_1_medicaid.csv", skip = 2, n_max = 52) |>
  select(-Footnotes) |>
  rename(state = Location) |>
  left_join(fips::fips, by = "state") |>
  select(state, fips, usps, everything()) |>
  gather(year, cutoff, -state:-usps) |>
  separate(year, c("month", "year")) |>
  mutate(type = "Medicaid", agegrp = "0-1") |>
  mutate(cutoff = as.numeric(cutoff) * 100) |>  # filter(is.na(cutoff))
  # TN 2000 and 2002 have not upper limits
  mutate(cutoff = if_else(usps == "TN" & year %in% c(2000, 2002), 9999, cutoff)) |>
  select(state, fips, usps, type, agegrp, everything()) |>
  print() -> infant0_1

read_csv("data-raw/children_age_1_5_medicaid.csv", skip = 2, n_max = 52) |>
  select(-Footnotes) |>
  rename(state = Location) |>
  left_join(fips::fips, by = "state") |>
  select(state, fips, usps, everything()) |>
  gather(year, cutoff, -state:-usps) |>
  separate(year, c("month", "year")) |>
  mutate(type = "Medicaid", agegrp = "1-5") |>
  mutate(cutoff = as.numeric(cutoff) * 100) |>  # filter(is.na(cutoff))
  # TN 2000 and 2002 have not upper limits
  mutate(cutoff = if_else(usps == "TN" & year %in% c(2000, 2002), 9999, cutoff)) |>
  select(state, fips, usps, type, agegrp, everything()) |>
  print() -> children1_5

read_csv("data-raw/children_age_6_18_medicaid.csv", skip = 2, n_max = 52) |>
  select(-Footnotes) |>
  rename(state = Location) |>
  left_join(fips::fips, by = "state") |>
  select(state, fips, usps, everything()) |>
  tidyr::gather(year, cutoff, -state:-usps) |>
  tidyr::separate(year, c("month", "year")) |>
  mutate(type = "Medicaid", agegrp = "6-18") |>
  mutate(cutoff = as.numeric(cutoff) * 100) |>  # filter(is.na(cutoff))
  # TN 2000 and 2002 have not upper limits
  mutate(cutoff = if_else(usps == "TN" & year %in% c(2000, 2002), 9999, cutoff)) |>
  select(state, fips, usps, type, agegrp, everything()) |>
  print() -> children6_18

read_csv("data-raw/children_age_0_18_chip.csv", skip = 2, n_max = 52) |>
  select(-Footnotes) |>
  rename(state = Location) |>
  left_join(fips::fips, by = "state") |>
  select(state, fips, usps, everything()) |>
  gather(year, cutoff, -state:-usps) |>
  separate(year, c("month", "year")) |>
  mutate(type = "CHIP", agegrp = "0-18") |>
  mutate(cutoff = as.numeric(cutoff) * 100) |>  # filter(is.na(cutoff)), No CHIP program
  select(state, fips, usps, type, agegrp, everything()) |>
  print() -> chip0_18

read_csv("data-raw/children_schip_mcaid.csv", skip = 2, n_max = 52) |>
  select(-Footnotes) |>
  rename(state = Location) |>
  left_join(fips::fips, by = "state") |>
  select(state, fips, usps, everything()) |>
  gather(year, cutoff, -state:-usps) |>
  separate(year, c("month", "year")) |>
  mutate(type = "CHIP/Mcaid Upper", agegrp = "0-18") |>
  mutate(cutoff = as.numeric(cutoff) * 100) |>  # filter(is.na(cutoff))
  # TN 2000 and 2002 have not upper limits
  mutate(cutoff = if_else(usps == "TN" & year %in% c(2000, 2002), 9999, cutoff)) |>
  select(state, fips, usps, type, agegrp, everything()) |>
  print() -> chip_mcaid_upper

infant0_1 |>
  bind_rows(children1_5) |>
  bind_rows(children6_18) |>
  bind_rows(chip0_18) |>
  bind_rows(chip_mcaid_upper) |>
  mutate(year = as.integer(year)) |>
  print() -> children

usethis::use_data(children, overwrite = TRUE)