How foreign investment in the middle-east collapsed after the revolution

fdi_arab_spring.R

# setup
set.seed(123)
library(tidyverse)
library(hrbrthemes)
library(ggplot2)
library(ggrepel)

# make the dataframe
df <-
  tibble::tribble(
    ~year, ~FDI, ~investment,
    2006, "Inflows", 70043,
    2007, "Inflows", 80291,
    2008, "Inflows", 88502,
    2009, "Inflows", 78283,
    2010, "Inflows", 70086,
    2011, "Inflows", 44842,
    2012, "Inflows", 52719,
    2013, "Inflows", 40509,
    2014, "Inflows", 31629,
    2015, "Inflows", 25690,
    2016, "Inflows", 32430,
    2017, "Inflows", 28711,
    2006, "Outflows", 22761,
    2007, "Outflows", 37401,
    2008, "Outflows", 44187,
    2009, "Outflows", 18923,
    2010, "Outflows", 21100,
    2011, "Outflows", 29546,
    2012, "Outflows", 21573,
    2013, "Outflows", 42498,
    2014, "Outflows", 16752,
    2015, "Outflows", 37251,
    2016, "Outflows", 36225,
    2017, "Outflows", 34984,
  ) %>%
  dplyr::mutate(.data = ., year = as.factor(year)) %>%
  dplyr::mutate(.data = ., investment = investment / 1000) %>%
  dplyr::mutate(.data = ., event = dplyr::case_when(
    year == "2010" & FDI == "Inflows" ~ "Arab Spring",
    TRUE ~ NA_character_
  ))

# plot
p <-
  ggplot(df, aes(year, investment, colour = FDI)) +
  geom_point(
    size = 4,
    alpha = 0.7,
    show.legend = FALSE
  ) +
  geom_path(aes(color = FDI, group = FDI)) +
  ggrepel::geom_label_repel(
    aes(label = investment),
    size = 4,
    show.legend = FALSE,
    family = "Roboto Condensed"
  ) +
  geom_vline(
    xintercept = "2010",
    linetype = "dashed",
    color = "#E7298AFF",
    size = 1,
    alpha = 0.5,
    na.rm = TRUE
  ) +
  geom_label(
    data = df,
    aes(x = "2010", y = 50, label = event),
    inherit.aes = FALSE,
    size = 5,
    color = "#E7298AFF",
    show.legend = FALSE,
    fontface = "bold",
    family = "Roboto Condensed"
  ) +
  hrbrthemes::theme_ipsum_rc() +
  scale_y_continuous(
    breaks = seq(0, 100, 10),
    labels = scales::dollar_format(suffix = "bn")
  ) +
  scale_color_manual(
    values = c("#1B9E77FF", "#D95F02FF"),
    guide = guide_legend(
      title = "",
      direction = "horizontal",
      label.position = "top",
      nrow = 1
    )
  ) +
  labs(
    title = "FDI inflows and outflows from MENA",
    subtitle = "(MENA: the Greater Middle East)",
    caption = substitute(paste(
      italic("Source"), ": Annual Investment Climate Report (2018)"
    )),
    y = "Foreign Direct Investment (FDI)"
  ) +
  theme(
    legend.position = "top",
    legend.justification = "left",
    legend.text = ggplot2::element_text(size = 12, face = "bold"),
    axis.title.x = ggplot2::element_text(size = 12, face = "bold"),
    axis.title.y = ggplot2::element_text(size = 12, face = "bold"),
    axis.text.x = ggplot2::element_text(size = 12, face = "bold"),
    axis.text.y = ggplot2::element_text(size = 12, face = "bold"),
    strip.text.x = ggplot2::element_text(size = 12, face = "bold"),
    strip.text.y = ggplot2::element_text(size = 12, face = "bold"),
    strip.text = ggplot2::element_text(size = 12, face = "bold"),
    plot.title = ggplot2::element_text(
      color = "black",
      size = 16,
      face = "bold"
    ),
    plot.caption = ggplot2::element_text(
      color = "black",
      size = 13,
      face = "plain"
    )
  )

# plot
plot(p)

# save the plot
ggplot2::ggsave(
  plot = p,
  filename = "fdi.png",
  width = 11,
  height = 9,
  dpi = 300
)