On the Fairness of the 2000 and 2016 Presidential Elections

What follows is an interesting thought experiment I thought I’d share. The two major candidates had roughly equal shares of the popular vote. (Red=47.3%, Blue=47.8%). What if the system was modified to take away the 2 bonus “senatorial” electoral votes from each state (and DC)? Well: Red votes => 306-2*30=246; Blue votes => 232-2*21=190. Red still gets the same disproportional amount of electoral votes! (Source: https://en.wikipedia.org/w/index.php?title=Special:CiteThisPage&page=United_States_presidential_election%2C_2016&id=749272989)

Here’s what I mean by same: Define D, the “distortion factor” in favor of the winner, as the ratio of received electoral votes to the number they would have had if electoral votes were perfectly proportional to popular vote. So D[Red, actual]=306/(.473*538)≈1.20 and D[Blue, actual]≈0.90. D[Red, modified]=246/(0.473*436)≈1.19, and D[Blue, modified]=190/(.478*436)≈0.91, which are essentially the same as before. You can also define G, the unfairness gap, as |D[red]-D[blue]|. G[actual]≈0.30, and G[modified]≈0.28, so we did manage to design a slightly more fair electoral tally.

I think that assigning electoral votes by congressional district would probably barely budge this result. The current House has a 247-188 Red majority, despite the fact that in 2014, Blue had a greater number of popular votes for House seats.

By contrast, in 2000, (the most recent other example of electoral college-popular vote mismatch) Red and Blue had similar proportions of the popular vote (47.9% Red, 48.4% Blue), but with Red only winning 271-266 in the electoral college (one elector abstained, Source: https://en.wikipedia.org/w/index.php?title=Special:CiteThisPage&page=United_States_presidential_election%2C_2000&id=749243397). D[Red, actual]=277/(0.479*538)≈1.07 and D[Blue, actual]=266/(0.484*538)≈1.02. G[actual, 2000]=0.05, a lot less unfair than this year, where G is approximately 0.30. In addition, it was still the case that Red had 30 states, giving 60 “senatorial” electoral votes; likewise Blue had 20 states and DC, just like in 2016. Run the same math as above and you get a Blue 211-222 electoral victory. D[red, modified]=211/(0.479*436)≈1.01 and D[blue, modified]=222/(.484*436)≈1.05. G[modified]≈0.04…so we only slightly reduced unfairness, however by making it unfair in Blue’s favor, and just happening to match up with the popular result.

The difference, of course, is that Red picked up some of the bigger states (by population) in 2016 that belonged to Blue in 2000, while Blue picked up fewer of Red’s big states. While it is clear 2016 was more unfair, as measured by D (distortion) and G (distortion gap, a.k.a., unfairness gap), the electoral college result is completely robust due to Red’s capturing of majority of the right states. Notwithstanding any concerns you may have about the particular Red candidate this year, if you accept the electoral college at all, I would say that Red’s victory this year is robust and legitimate.


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