R Econ Visual Library

# Install and load packages ---------------
packages <- c(
  "tidyverse",
  "ggrepel",
  "WDI",
  "forcats",
  "scales"
)

# Change to install = TRUE to install the required packages
pacman::p_load(packages, character.only = TRUE, install = FALSE)

# Load an example dataset ---------------
data <- WDI(indicator = "NY.GDP.PCAP.KD", start = 1980, end = 2012)
country_code <- as_tibble(WDI_data$country)

data <- data %>%
  rename(GDP = NY.GDP.PCAP.KD) %>%
  inner_join(country_code, by = "country") %>%
  filter(year %in% c(1980, 2012), region != "NA") %>%
  group_by(iso3c) %>%
  pivot_wider(names_from = "year", values_from = "GDP") %>%
  ungroup()

country_stress <- c("USA", "CHN", "BRA", "RWA")

ggplot(data, aes(x = `1980`, y = `2012`)) + 
  geom_point(aes(alpha = 0.8, color = (iso3c %in% country_stress)), show.legend = FALSE) +
  geom_abline(slope = 1, color = "gray") +
  geom_text_repel(aes(label = ifelse(iso3c %in% country_stress, iso3c, ""))) +
  scale_y_log10(
    limits = c(8e+1, 3e+5),
    breaks = c(1e+2, 1e+3, 1e+4, 1e+5),
    labels = expression(10^2, 10^3, 10^4, 10^5)
  ) +
  scale_x_log10(
    limits = c(8e+1, 3e+5),
    breaks = c(1e+2, 1e+3, 1e+4, 1e+5),
    labels = expression(10^2, 10^3, 10^4, 10^5)
  ) +
  scale_color_manual(values = c("gray", "red")) +
  xlab("GDP per capita (constant 2000 US$) in 1980") +
  ylab("GDP per capita (constant 2000 US$) in 2012") +
  theme_classic() +
  theme(
    axis.text = element_text(size = 12),
    axis.title = element_text(size = 12)
  )