rba_ur_forecast.R

library(readrba)
library(readabs)
library(tidyverse)
library(gganimate)
library(ggdirectlabel)

min_date <- ymd("1990-01-01")

unemp_forecasts <- read_forecasts() |>
  filter(
    series == "unemp_rate",
    date >= min_date
  ) |> 
  select(date, forecast_date, value) |> 
  mutate(series = "RBA forecast")

ur_actual <- read_abs_series("A84423050A") |>
  filter(date >= min_date) |>
  select(date, value) |> 
  mutate(series = "Actual")

unemp_comb <- unemp_forecasts |> 
  bind_rows(ur_actual) 

unemp_comb |> 
  ggplot(aes(x = date, y = value, group = forecast_date, col = series)) +
  geom_line(aes(alpha = series,
                linewidth = series)) +
  geom_richlegend(aes(label = series),
                  size = 16 / .pt,
                  family = "Roboto Condensed") +
  scale_y_continuous(labels = \(x) paste0(x, "%"),
                     breaks = seq(0, 20, 1)) +
  scale_alpha_manual(values = c("Actual" = 1,
                                "RBA forecast" = 0.66)) +
  scale_linewidth_manual(values = c("Actual" = 1,
                                    "RBA forecast" = 0.5)) +
  theme_minimal(base_size = 16,
                base_family = "Roboto Condensed") +
  theme(legend.position = "none",
        axis.title = element_blank(),
        panel.grid.minor = element_blank(),
        plot.caption = element_text(size = 8)) +
  labs(subtitle = "Unemployment rate (Australia), actual and forecast",
       caption = "Source: RBA and ABS. Seasonally adjusted. RBA forecasts are for quarter-averages, actual data is monthly.")