script to look at federal spending by year

cpi_adj_outlays.R

library(tidyverse)
library(zoo)

dat = read_csv('~/Desktop/selected_outlays_2025-04-10.csv') %>%
  select(date, spend = `Cumulative year-to-date`) 
  

dat = tibble(
  date = ymd(as_date(min(dat$date):max(dat$date)))
) %>%
  left_join(dat)

dat = dat %>% 
  mutate(year = as.character(year(date)),
         spend = na.locf(spend, na.rm = T)) %>%
  group_by(year) %>%
  mutate(day = as.numeric(date - min(date))) %>%
  ungroup()

ggplot(dat, aes(x = day, y = spend, col = year)) + 
  geom_line()

# adjust for inflation
cpi = read_csv('https://fred.stlouisfed.org/graph/fredgraph.csv?bgcolor=%23ebf3fb&chart_type=line&drp=0&fo=open%20sans&graph_bgcolor=%23ffffff&height=450&mode=fred&recession_bars=on&txtcolor=%23444444&ts=12&tts=12&width=1320&nt=0&thu=0&trc=0&show_legend=yes&show_axis_titles=yes&show_tooltip=yes&id=CPIAUCSL&scale=left&cosd=1947-01-01&coed=2025-03-01&line_color=%230073e6&link_values=false&line_style=solid&mark_type=none&mw=3&lw=3&ost=-99999&oet=99999&mma=0&fml=a&fq=Monthly&fam=avg&fgst=lin&fgsnd=2020-02-01&line_index=1&transformation=lin&vintage_date=2025-04-10&revision_date=2025-04-10&nd=1947-01-01') %>%
  set_names(., c('date', 'cpi')) %>%
  filter(date >= min(dat$date))

cpi = tibble(
  date = ymd(as_date(min(dat$date):max(dat$date)))
) %>%
  left_join(cpi) %>%
  mutate(cpi = na.locf(cpi))

dat = dat %>% left_join(cpi, by = 'date')

# calculate cumulative inflation over year
dat = dat %>% 
  mutate(cumulative_cpi_change = cpi / first(cpi)) %>%
  ungroup()

# deflate spending
dat = dat %>% mutate(cpi_adj_spend = spend / cumulative_cpi_change)

# plot
dat %>% filter(day <= 30*6) %>%
  ggplot(., aes(x = day, y = cpi_adj_spend, col = year)) + 
  geom_line()

# transform for output
out = dat %>% filter(day <= 30*6) %>%
  select(day, year, cpi_adj_spend) %>%
  spread(year, cpi_adj_spend) %>%
  select(day, `2024`, `2025`) %>%
  mutate_all(na.locf, na.rm = T)


write_csv(out, '~/Desktop/out.csv')

out.csv

selected_outlays_2025-04-10.csv