jan_ur_delta.R

library(readabs)
library(tidyverse)

ur <- read_abs_series("A84423050A") |> 
  select(date, ur = value)

dec_jan_moves <- ur |> 
  mutate(diff = ur - lag(ur, n = 1L, order_by = date)) |> 
  filter(month(date) == 1L) |> 
  mutate(is_latest = if_else(date == max(date), "Jan '23", "Other Januaries since 1979")) 

ave_diff = mean(dec_jan_moves$diff)

dec_jan_moves |> 
  ggplot(aes(x = diff, fill = is_latest, col = is_latest)) +
  geom_vline(xintercept = ave_diff) +
  annotate("text", x = ave_diff, y = 0.95,
           label = paste0("Mean: ", round(ave_diff, 2), " ppts"),
           hjust = -0.1) +
  ggdist::geom_dots(group = 1) +
  theme_minimal(base_size = 18) +
  scale_y_continuous(expand = expansion(c(0, 0.05))) +
  theme(axis.text.y = element_blank(),
        legend.position = "top",
        legend.direction = "horizontal",
        legend.title = element_blank(),
        axis.title.y = element_blank()) +
  labs(x = "Change in unemp rate between Dec and Jan (ppts)",
       caption = "Note: Based on seasonally adjusted data.\nSource: ABS")

dec_jan_moves |> 
  mutate(is_latest = if_else(date == max(date), "Jan '23", "Other Januaries since 1979")) |> 
  ggplot(aes(x = year(date), y = diff, fill = is_latest, col = is_latest)) +
  geom_col() +
  theme_minimal(base_size = 18) +
  scale_y_continuous(expand = expansion(c(0, 0.05))) +
  theme(axis.title.x = element_blank(),
        legend.position = "top",
        legend.direction = "horizontal",
        legend.title = element_blank(),
        axis.title = element_blank()) +
  labs(subtitle = "Change in unemp rate between Dec and Jan (ppts)",
       caption = "Note: Based on seasonally adjusted data.\nSource: ABS")