coalitions

Overview

The coalitions package implements a Bayesian framework for the estimation of event probabilities in multi-party electoral systems (Bauer and others, 2019). To support estimation the package also implements scrappers that obtain data for German federal and general elections as well as Austrian general election. The implementation can be extended to support other elections.

• To get started, see our workflow vignette

• Check out our interactive shiny app on

German (state and federal) elections/surveys

• Updates are available from our KOALA_LMU twitter account!

Installation

# To install from CRAN use:
install.packages("coalitions")

# To install the most current version from GitHub use:
devtools::install_github("adibender/coalitions")

Usage

Detailed workflow is outlined in the workflow vignette.

A short overview is presented below.

Scrape surveys

The wrapper get_surveys() which takes no arguments, downloads all surveys currently available at wahlrecht and stores them in a nested tibble:

library(coalitions)
library(dplyr)
library(tidyr)
surveys <- get_surveys()
surveys

## # A tibble: 7 x 2
##   pollster   surveys
##   <chr>      <list>
## 1 allensbach <tibble [42 × 5]>
## 2 emnid      <tibble [226 × 5]>
## 3 forsa      <tibble [236 × 5]>
## 4 fgw        <tibble [84 × 5]>
## 5 gms        <tibble [96 × 5]>
## 6 infratest  <tibble [110 × 5]>
## 7 insa       <tibble [305 × 5]>

Each row represents a polling agency and each row in the surveys column again contains a nested tibble with survey results from different time-points:

surveys %>%
    filter(pollster == "allensbach") %>%
    unnest()

## # A tibble: 42 x 6
##    pollster   date       start      end        respondents survey
##    <chr>      <date>     <date>     <date>           <dbl> <list>
##  1 allensbach 2018-02-23 2018-02-02 2018-02-15        1271 <tibble [7 × 3…
##  2 allensbach 2018-01-25 2018-01-05 2018-01-18        1221 <tibble [7 × 3…
##  3 allensbach 2017-12-21 2017-12-01 2017-12-14        1443 <tibble [7 × 3…
##  4 allensbach 2017-11-30 2017-11-22 2017-11-27        1299 <tibble [7 × 3…
##  5 allensbach 2017-10-25 2017-10-07 2017-10-19        1454 <tibble [7 × 3…
##  6 allensbach 2017-09-22 2017-09-13 2017-09-20        1074 <tibble [7 × 3…
##  7 allensbach 2017-09-19 2017-09-06 2017-09-14        1083 <tibble [7 × 3…
##  8 allensbach 2017-09-06 2017-08-22 2017-08-31        1043 <tibble [7 × 3…
##  9 allensbach 2017-08-22 2017-08-04 2017-08-17        1421 <tibble [7 × 3…
## 10 allensbach 2017-07-18 2017-07-01 2017-07-12        1403 <tibble [7 × 3…
## # ... with 32 more rows

survey <- surveys %>% unnest() %>% slice(1)
survey %>% unnest()

## # A tibble: 7 x 8
##   pollster   date       start      end        respondents party  percent
##   <chr>      <date>     <date>     <date>           <dbl> <chr>    <dbl>
## 1 allensbach 2018-02-23 2018-02-02 2018-02-15        1271 cdu      32.0
## 2 allensbach 2018-02-23 2018-02-02 2018-02-15        1271 spd      17.5
## 3 allensbach 2018-02-23 2018-02-02 2018-02-15        1271 greens   12.0
## 4 allensbach 2018-02-23 2018-02-02 2018-02-15        1271 fdp      11.0
## 5 allensbach 2018-02-23 2018-02-02 2018-02-15        1271 left      9.50
## 6 allensbach 2018-02-23 2018-02-02 2018-02-15        1271 afd      13.0
## 7 allensbach 2018-02-23 2018-02-02 2018-02-15        1271 others    5.00
## # ... with 1 more variable: votes <dbl>

Calculate coalition probabilities

For each survey (row) we can calculate the coalition probabilities

survey %>% get_probabilities(nsim=1e4) %>% unnest()

## # A tibble: 6 x 4
##   pollster   date       coalition       probability
##   <chr>      <date>     <chr>                 <dbl>
## 1 allensbach 2018-02-23 cdu                  0
## 2 allensbach 2018-02-23 cdu_fdp              0.0500
## 3 allensbach 2018-02-23 cdu_fdp_greens     100.0
## 4 allensbach 2018-02-23 spd                  0
## 5 allensbach 2018-02-23 left_spd             0
## 6 allensbach 2018-02-23 greens_left_spd      0

References

Bauer, Alexander, Andreas Bender, André Klima, and Helmut Küchenhoff. 2019. “KOALA: A New Paradigm for Election Coverage.” AStA Advances in Statistical Analysis, June. https://doi.org/10.1007/s10182-019-00352-6.

Bender, Andreas, and Alexander Bauer. 2018. “Coalitions: Coalition Probabilities in Multi-Party Democracies,” March. https://doi.org/10.21105/joss.00606.