Confession time. One of my favorite subreddits on reddit is r/mapporn; a subreddit dedicated to the most visually appealing maps from all historical periods and dealing with a variety of topics. We, at QP, cannot get our fill of maps as we (especially Michael Flynn) have blogged about it a few times (see here, here, and here). Yesterday, this map of leadership tenure was posted from The Economist:
The cutoff date of 1945 seems like a controversial choice and the single image of the map did not come with clear coding rules as how to decisions were made. Being familiar with the Archigos data project put together by Kristian Skrede Gleditsch and Giacomo Chiozza (paper here), I figured this was an easy task to replicate to see what a common political science data set says about leadership tenure (one that I have used in my own research). To replicate this, I created 1/1/1945 as the cutoff point and any existing regime is assumed to start freshly on that date (an untenable assumption of course). This left me with the number of days of leadership that I divided by 365.24 (Leap years could be off, so I averaged the year length). Then, by averaging out the leadership tenure for this time period until 2004, created a range of values for each country. In Stata, creating a choropleth map is not overly difficult using spmap package and two different guides found here and here.
Post-1945 Replication:
The pastel color provides a bit more contrast and makes the missing data cases easily identifiable. Some of this may be due to a quick use of the kountry package an dmissing a few obvious lacking cases. Additionally, the data in Archigos goes back to 1875, so replicating the map again using the full data set is possible and done here:
Expanding the data backwards introduces a bit more variation than just starting from 1945. Naturally, with two wold wars included, leadership turnover may be expected to be shorter in some countries. Of note, the US average jumps up a category.
Update: By request, a few maps that are more colorblind friendly. Blue:
Greyscale:
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