VIZ <- p_dat %>% 
  select(year, sex, dom, type, n, m, exp_tot) %>%
  filter(year %in% par$pint, dom == "ch", type == "alt") %>% 
  dplyr::summarize(m = weighted.mean(m, n), n = sum(n),
                   .by = c("year", "dom")) %>% 
  mutate(wf_n = n / lag(n) - 1)

POP <- pop %>% 
  filter(age >= 65) %>% 
  dplyr::summarize(n = sum(pop))

ggplot(VIZ, aes(x = year, y = n, col = as.factor(dom))) +
  geom_line(alpha = .5) +
  geom_shadowpoint() +
  scale_colour_viridis_d()
  

sh <-
  left_join(pop, pen_n, by = c("year", "sex", "nat", "age"),
            relationship = "one-to-many") %>%
  # Select most recent STATPOP year.
  filter(year %in% (first(par$pint) - 10):first(par$pint), type == "alt") %>%
  mutate(share = n / pop) %>%
  select(- year, - pop, - n) %>% 
  filter(age >= 65)

VIZ <- sh %>% 
  filter(age == 65) %>% 
  dplyr::summarize(share = weig)
