forecasts_cf_previous_nostyling.R

library(tidyverse)
library(readrba)

forecasts <- rba_forecasts()

latest_two <- forecasts |>
  filter(forecast_date %in% c(max(forecast_date),
                              max(forecast_date) - months(3)))

latest_two |>
  filter(!series_desc %in% c("Gross national expenditure", "Public demand",
                             "Imports", "Terms of trade", "Exports",
                             "Major trading partner (export-weighted) GDP",
                             "Dwelling investment")) |>
  mutate(forecast_date = format(forecast_date, "%b %Y")) |>
  ggplot(aes(x = date, y = value, col = forecast_date)) +
  geom_line() +
  scale_y_continuous(breaks = \(x) scales::breaks_pretty(3)(x)) +
  guides(colour = guide_legend(title = "Forecast issued: ")) +
  facet_wrap(~series_desc, scales = "free_y",
             nrow = 2,
             labeller = label_wrap_gen(18)) +
  theme_minimal(base_family = "Roboto",
                base_size = 12) +
  theme(legend.position = "top",
    legend.title = element_text(),
    axis.title = element_blank(),
    axis.text.y = element_text(size = 10),
    plot.margin = margin(5, 10, 5, 5),
    panel.grid.minor = element_blank(),
    strip.text = element_text(size = 10)) +
  labs(title = "Unemployment is expected to rise further and faster than previously forecast",
       subtitle = paste0("RBA's forecasts issued in ",
                         unique(latest_two$forecast_date) |>  format("%B %Y") |>  paste(collapse = " and ")),
       caption = "Source: RBA Statement on Monetary Policy")

ggsave("rba.png", width = 20, height = 15, units = "cm", bg = "white", dpi = "retina")