Cost of governing for populist parties

pop_cog.R

library(here)
library(tidyverse)
library(colorspace)
library(RColorBrewer)
library(hrbrthemes)

set.seed(2686)

here::i_am("R/rr_cog.R")

elex <- read.csv(here::here("data", "view_election.csv"))

### Create year to use later
elex <- elex |>
    mutate(election_date = as.Date(election_date),
           year = as.numeric(format(election_date, "%Y")))

### Just entries from the post-1945 period
elex <- elex |>
    filter(year >= 1945) |>
    filter(election_type == "parliament")


### Calculate change in vote share by a self-join, using the previous
### election ID as key.
elex <- left_join(elex,
                  elex |> distinct(election_id, party_id, vote_share),
                  by = join_by(previous_parliament_election_id == election_id,
                               party_id == party_id),
                  suffix = c("", ".lagged"))

### Remove cases where that party doesn't have a previous vote share
elex <- elex |>
    mutate(delta = vote_share - vote_share.lagged) |>
    ungroup() |>
    filter(!is.na(delta))

### Remove the 1981 Cyprus election, where a party is recorded as
### having lost a lot because an alliance splintered
elex <- elex |>
    filter(election_id != 70)

### Get cabinet
### status
cabs <- read.csv(here::here("data", "view_cabinet.csv")) |>
    dplyr::select(cabinet_id, party_id, cabinet_party)

elex <- left_join(elex,
                  cabs,
                  by = join_by(previous_cabinet_id == cabinet_id,
                               party_id == party_id))

### Remove instances where we don't know whether they were a cabinet party
elex <- elex |>
    filter(!is.na(cabinet_party))

## Filter to countries in the popuLust
populist_countries <- c("AUT", "BEL", "BGR", "HRV", "CYP",
                        "CZE", "DNK", "EST", "FIN", "FRA",
                        "DEU", "GRC", "HUN", "ISL", "IRL",
                        "ITA", "LVA", "LTU", "LUX", "NLD",
                        "NOR", "POL", "PRT", "ROU", "SVK",
                        "SVN", "ESP", "SWE", "CHE", "GBR")

elex <- elex |>
    filter(country_name_short %in% populist_countries)

### Add on the populist
populist <- read.delim(here::here("data",
                                  "The PopuList 3.0.csv"),
                       sep = ";")

populist <- populist |>
    dplyr::select(parlgov_id, populist,
                  populist_start,
                  populist_end)

### Join 
elex <- left_join(elex, populist,
                  by = join_by(party_id == parlgov_id,
                               year >= populist_start,
                               year <= populist_end))

### If they're not in the populist, they're not populist
elex <- elex |>
    mutate(populist = coalesce(populist, 0L))

elex <- elex |>
    mutate(type = case_when(populist == 1 & cabinet_party == 1 ~ "Populist party IN government",
                            
                            populist == 1 & cabinet_party == 0 ~ "Populist party OUT OF government",
                            populist == 0 & cabinet_party == 1 ~ "Non-populist party IN government",
                            populist == 0 & cabinet_party == 0 ~ "Non-populist party OUT OF government",
                            TRUE ~  "Missing data"),
           type = factor(type,
                         levels = c("Populist party IN government",
                                    "Non-populist party IN government",
                                    "Populist party OUT OF government",
                                    "Non-populist party OUT OF government"),
                         ordered = TRUE))

my_pal <- brewer.pal(4, "Paired")
### Rearrange
my_pal <- my_pal[c(2, 4, 1, 3)]

my_comparisons <- list( c("Populist party IN government",
                          "Non-populist party IN government"))

p <- ggplot(elex, aes(x = type, y = delta, colour = type, fill = type)) +
    scale_x_discrete("") +
    scale_y_continuous("Change in vote share between consecutive elections in percentage points",
                       limits = c(-50, NA)) +
    geom_hline(yintercept = 0) + 
    geom_boxplot(width = 0.5) +
    scale_fill_manual(values = my_pal,
                      guide = "none") +
    scale_colour_manual(values = darken(my_pal, 0.3),
                          guide = "none") +
    coord_flip() +
    stat_compare_means(comparisons = my_comparisons, label = "p.signif") + 
    labs(title = "Populist parties lose votes when in government like all other parties",
         subtitle = "No significant differences in governing party losses comparing populist to non-populist parties",
         caption = "Data: ParlGov / PopuList v3.0") + 
    theme_ipsum_rc() +
    theme(plot.title.position = "plot")

ggsave(p, file = "populist_losses.png", width = 9, height = 6, dpi = 96, bg = "white")