chrishanretty

### Load the necessary libraries
library(sf)
library(tidyverse)

### Read in the shapefile
### Downloaded from https://geoportal.statistics.gov.uk/datasets/ons::local-authority-districts-december-2022-boundaries-uk-bfc/explore?location=55.215430%2C-3.316939%2C6.61
lad_shp <- st_read("LAD_DEC_2022_UK_BFC.shp")

### Read in the list of coordinates
### 

chrishanretty

library(vdemdata)
library(tidyverse)
library(ggflags)
library(countrycode)
library(hrbrthemes)
### Get the V-Dem data in
data("vdem")
dat <- vdem |>
    distinct(country_name, country_text_id, year,
             v2x_polyarchy, v2x_polyarchy_sd) |>

chrishanretty

library(tidyverse)
library(hrbrthemes)

### This section reads in the data -- scroll down for the code that
### generates the figures and the graphics


tibble::tribble(
  ~aye_vote, ~ONSConstID,                             ~Constituency,                          ~MP,             ~Party, ~ConstyOpposition, ~ConstyOpposition_sd,
          1, "E14000530",                               "Aldershot",               "Leo Docherty",     "Conservative",  1.67320394423204,   0.0170138236227471,

chrishanretty

### Purpose of this code: plot the proportion of people in each CSES
### wave 5 study who can place themselves on a left-right scale.

### You will need to have downloaded the CSES 5 data somewhere
library(tidyverse)
library(ggtext)
library(RColorBrewer)
library(countrycode)
library(hrbrthemes)

chrishanretty

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

dat <- read.csv("view_cabinet.csv")

dat <- dat %>%
    group_by(country_name_short,
             country_id,
             election_date,

chrishanretty

### Replicate 
### 
### Kim, Nam Kyu. "Previous Military Rule and Democratic Survival." Journal of Conflict Resolution 65, no. 2-3 (2021): 534-562
###
### including an additional covariate for a hereditary head of state
### 
library(rio)
library(tidyverse)
library(vdemdata)
library(countrycode)

chrishanretty

library(tidyverse)
library(rio)
library(hrbrthemes)

### (1) Get files in
### Parish to Ward
### https://geoportal.statistics.gov.uk/datasets/ons::parish-to-ward-to-local-authority-district-december-2020-lookup-in-england-and-wales-v2/about

par2ward <- read.csv("Parish_to_Ward_to_Local_Authority_District__December_2020__Lookup_in_England_and_Wales_V2.csv")
par2ward$FID <- NULL

chrishanretty

library(tidyverse)
library(cmdstanr)
library(MCMCpack)

### log PDF is based on eqn. 3 in https://www2.seas.gwu.edu/~dorpjr/Publications/Bookchapter/MarcelDekker2003.pdf
stan_code <-
"
functions {
    real orddir_lpdf(vector y, real[] alpha) {
    int K = size(alpha);

chrishanretty

library(countrycode)
library(tidyverse)
library(rio)

holder <- list()

### (0) PartyFacts lookup
pf <- read.csv("data/partyfacts-external-parties.csv")

### (1) Manifesto Project

chrishanretty

### Let's generate some data with a step function
library(mgcv)
set.seed(1116)

nDays <- 200
day <- 1:nDays

y <- rnorm(200, 1, 0.25) + I(day > 100) * -0.5

y <- ifelse(y < 0,