Women's empowerment in graphs

iwd.R

library(vdemdata)
library(tidyverse)
library(hrbrthemes)
library(ggtext)

data("vdem")
vdem <- vdem |>
    filter(year > 1945)

### Plot trends in v2lgfemleg
p1 <- ggplot(vdem, aes(x = year,
                 y = v2lgfemleg)) +
    geom_path(aes(group = country_text_id),
              alpha = 1/8) +
    scale_x_continuous("Year") +
    scale_y_continuous("Proportion of lower chamber legislators who are women") + 
    geom_smooth(se = FALSE) +
    labs(title = "Women's representation in parliaments has increased...",
         subtitle = "Each line represents a country; blue line gives the average trend across countries",
         caption = "Data: V-Dem Project, variable <span style = 'font-family: monospace'>v2lgfemleg</span>") + 
    theme_ipsum_rc() +
    theme(plot.caption = element_markdown())

### Plot trends in v2pepwrgen
p2 <- ggplot(vdem, aes(x = year,
                 y = v2pepwrgen)) +
    geom_path(aes(group = country_text_id),
              alpha = 1/8) +
    scale_x_continuous("Year") +
    scale_y_continuous("Power distributed by gender\n(higher values indicate greater equality)") + 
    geom_smooth(se = FALSE) +
    labs(title = "Even while women's share of power has plateaued...",
         subtitle = "Each line represents a country; blue line gives the average trend across countries",
         caption= "Data: V-Dem project, variable <span style = 'font-family: monospace'>v2pepwrgen</span>") + 
    theme_ipsum_rc() +
    theme(plot.caption = element_markdown())

### Year on year correlations between the two
plot_df <- vdem |>
    dplyr::select(year, country_text_id, v2pepwrgen, v2lgfemleg) |>
    nest(data = c(country_text_id, v2pepwrgen, v2lgfemleg)) |>
    mutate(the_cor = map_dbl(data, function(df)cor(df$v2pepwrgen, df$v2lgfemleg, use = "pairwise")),
           the_cor_lo = map_dbl(data, function(df)cor.test(df$v2pepwrgen, df$v2lgfemleg, use = "pairwise")$conf.int[1]),
           the_cor_hi = map_dbl(data, function(df)cor.test(df$v2pepwrgen, df$v2lgfemleg, use = "pairwise")$conf.int[2])
           )

p3 <- ggplot(plot_df, aes(x = year, y = the_cor,
                          ymin = the_cor_lo,
                          ymax = the_cor_hi)) +
    geom_pointrange(size = .5, colour = "darkgrey", alpha = 2/3) +
    scale_x_continuous("Year") +
    scale_y_continuous("Correlation between representation and equality of power",
                       limits = c(0, NA)) +
    labs(title = "... because the association between legislative \nrepresentation and power varies over time") + 
    theme_ipsum_rc()

ggsave(p1,
       file = "p1.png",
       width = 7, height = 5,
       bg = "white",
       type = "Cairo")

ggsave(p2,
       file = "p2.png",
       width = 7, height = 5,
       bg = "white",
       type = "Cairo")

ggsave(p3,
       file = "p3.png",
       width = 7, height = 5,
       bg = "white",
       type = "Cairo")