Plot relationship between inequality and democracy

ineq_changes.R

### This uses code from Marta Kolczynska
### https://martakolczynska.com/post/participation-inequality-indices/

library(rio)
library(tidyverse)
library(vdem)
library(countrycode)
library(hrbrthemes)

vdem_part <- extract_vdem(name_pattern = "v2x_libdem",
                          include_uncertainty = FALSE) %>%
    select(iso3 = vdem_country_text_id,
           year,
           vdem_par = v2x_libdem)

swiid <- read.csv("https://raw.githubusercontent.com/fsolt/swiid/master/data/swiid7_1_summary.csv",
                  stringsAsFactors = FALSE, encoding = "UTF-8") %>%
    mutate(iso3 = countrycode(country, "country.name", "iso3c")) %>%
    mutate(iso3 = ifelse(country == "Kosovo", "XKX", iso3)) %>%
    select(iso3, year, gini_disp)

dat <- merge(vdem_part, swiid)

most_recent <- dat %>%
    group_by(iso3) %>%
    arrange(desc(year)) %>%
    filter(row_number() == 1)

mod0 <- lm(vdem_par ~ gini_disp, data = most_recent)
mod1 <- lm(vdem_par ~ poly(gini_disp, 2), data = most_recent)

p1 <- ggplot(most_recent, aes(x = gini_disp, y= vdem_par)) +
    geom_hline(yintercept = 0) + 
    geom_point() +
    geom_point(data = subset(most_recent, iso3 == "GBR"),
               colour = "red",
               size = 2) + 
    scale_x_continuous("Gini coefficient\n(0-100; higher values indicate greater inequality") +
    scale_y_continuous("V-Dem measure of liberal democracy\n(0-1; higher values indicate greater democracy",
                       limits = c(0, 1)) +
    geom_smooth(method = "lm", formula = y ~ poly(x, 2), se = FALSE) +
    theme_ipsum_rc() +
    labs(title = "The relationship between inequality and democracy is not straightforward",
         subtitle = "The most democratic countries are most equal, but some highly unequal countries are also moderately democratic",
         caption = "Data: \nV-Dem Project @vdeminstitute\nStandardized World Income Inequality Database @fredericksolt")

ggsave(p1, file = "ineq_levels.png",
       width = 1024/300, height = 512/300,
       units = "in", dpi = 300, scale = 5)

### Now look at changes
pad <- function(x, len) {
    if (length(x) != len) {
        return(rep(NA, len))
    } else {
        return(x)
    }
}

changes <- dat %>%
    group_by(iso3) %>%
    arrange(desc(year)) %>%
    filter(row_number() %in% c(1, 20)) %>%
    mutate(vdem_chg = pad(-diff(vdem_par), 1),
           gini_chg = pad(-diff(gini_disp), 1)) %>%
    filter(row_number() == 1) %>%
    filter(!is.na(gini_chg)) %>%
    filter(!is.na(vdem_chg))

mod0 <- lm(vdem_chg ~ gini_chg, data = changes)
mod1 <- lm(vdem_chg ~ poly(gini_chg, 2), data = changes)
mod2 <- lm(vdem_chg ~ poly(gini_chg, 3), data = changes)

p2 <- ggplot(changes, aes(x = gini_chg, y= vdem_chg)) +
    geom_point() +
    geom_point(data = subset(changes, iso3 == "GBR"),
               colour = "red",
               size = 2) +
    geom_hline(yintercept = 0) +
    geom_vline(xintercept = 0) + 
    scale_x_continuous("Change in Gini coefficient\n(higher values indicate country become more unequal") +
    scale_y_continuous("Change in V-Dem measure of liberal democracy\n(positive values indicate country became more democratic") +
    geom_smooth(method = "lm", formula = y ~ poly(x, 1), se = FALSE) +
    theme_ipsum_rc() +
    labs(title = "Changes in inequality over the past twenty years are not related to changes in democracy",
         subtitle = "")

ggsave(p2, file = "ineq_changes.png",
       width = 1024/300, height = 512/300,
       units = "in", dpi = 300, scale = 5)