Germany is important not only because it is our biggest neighbor, but it plays an important role in the European Union as well. Therefore the outcome of the elections is important. The turnout of the latest elections for a new Bundestag was published by most media. I was impressed by the data journalism approach of the Economist.
Here is a copy of one of the visualizations in the article.
The interesting issue is that if you count up the seats you get 734, and the old parliament had 709.
The size of the Bundestag varies. How does this work? Well is complicated; and is related to to votes the first vote(for a person) and the second vote(for a party). But how do you calculate the number of seats in the Bundestag? Of course it is statistics and at R-blogger I found the answer.
Here are the links to the articles:
Both articles explain the logic behind the calculation of the seats. The actual calculation is done through a piece of software: seat-calculator.R
And the piece of code that does the tric look as follows:
dat = read.csv("results_2021.csv",encoding="UTF-8") %>%
res = compute.seats(dat)
## Total size: 734 seats
## # A tibble: 7 x 5
## party vote_share seat_shares seats ueberhang
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 SPD 0.282 0.281 206 0
## 2 CDU 0.207 0.206 151 0
## 3 Gruene 0.162 0.161 118 0
## 4 FDP 0.126 0.125 92 0
## 5 AfD 0.113 0.113 83 0
## 6 CSU 0.0567 0.0613 45 3
## 7 Linke 0.0536 0.0531 39 0
The conclusion is:
“For me it feels not like a well designed election system if a single electoral district can have such huge impact on the size of the parliament…” And in some situations a parliament of more than 900 seats is possible. “That would be a gigantic, very crowded and expensive parliament”.
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