The Gini coefficient is a statistical tool to measure income inequality within societies by comparing the real wealth distribution within that society with a theoretic equal distribution of the total wealth.
Steemit's Gini coefficient is 76 and therefore on par with Subsahara Africa and South America.
Today I was made aware of the Steemit Whales Service, where all users of Steemit are listed with their reputation, their Steem Dollars, their Steem Power and the total estimated value of their account. When I saw it I thought it is possible and might be interesting to see what Gini coefficient Steemit has.
Unfortunately, the site only displays 250 users at once which is why I only included the most valuable 1,000 accounts into the calculation. Despite that, the results are very telling.
The Gini Coefficient And My Approach Explained
- First I copy+pasted the first 40 pages with the biggest 1,000 Steemit Whales into a spread sheet. You can download it here or here.
- After checking for errors I listed them by value starting with the lowest and partitioned them in 10 deciles.
- Then I calculated the respective total value of every decile plus the total value of all 1,000 accounts and divided that through 10 to get to the average value of every decile.
- As next step I calculated the decile values as percentage of the total value (in the spreadsheet "% of Decile Equally Distributed" and "% of Decile In Reality").
- At first I aggregated the decile values in percentage and created the chart.
- And after that I subtracted the real values of the deciles from the average values of the deciles (also percentage).
- The results of the subtraction aggregated are the Gini coefficient.
The examples for the Gini coefficient I found used quartiles, but I don't think using deciles makes the result worse.
Steemits Gini Coefficient Is Concerning - And I Only Calculated It For The Top Ranks!
A Gini coefficient of 76% that I have calculated is worse than anything planet earth has to offer. It's comparable to a billionaire in his helicopter flying low over a slum in Caracas or Lagos. If you take him, his pilots and the million poor souls who live below them in the slum, then you probably get the same number.
The countries with the biggest income inequality according to a list on Wikipedia plus Steemit and its theoretic spot in the world.
I guess this situation is a normal sign of a brand new and growing place in the virtual space that is still finding itself. In the long run of course this massive inequality in the wealth distribution quite likely won't be a good thing. It might drive away new users when they realize that the cake has already been eaten.
On the other hand, the Gini coefficient is not perfect and no proof, but only an indicator that something is in disarray.
And it also could be of course that I have made a mistake in the calculation. Although considering the result - maybe I should hope that and the real result shows a bit more cohesion.