Biden won the last election by 42,918 combined votes in three swing states. Trump won the election before that by 77,744 votes. 537 votes in Florida decided the 2000 election.
along with:
generate net swing-state votes this election range from a few hundred to several thousand dollars per vote
You get that the entire election outcome can be purchased for ~$13M - $600M.
But I’m assuming it isn’t actually isn’t that cheap to swing the election?
Well, it implies you could change the election with those amounts if you knew exactly how close the election would be in each state and spent optimally. But If you figure the estimates are off by an OOM, and half of your spending goes to states that turn out not to be useful (which matches a ~30 min analysis I did a few months ago), and you have significant diminishing returns such that $10M-$100M is 3x less impactful than the first $10M and $100M-$1B is another 10x less impactful, you still get:
First $10M is ~$10k per key vote = 1,000 votes (enough to swing 2000)
Next $90M is ~$30k per key vote = 3,000 votes
Next $900M is ~$90k per key vote = 10,000 votes
I think if you think there’s a major difference between the candidates, you might put a value on the election in the billions—let’s say $10B for the sake of calculation; so the first $10M would be worth it if there’s a 0.1% chance the election is decided by <1000 votes (which of course happened 6 elections ago!), the next $90M is worth it if there’s a 0.9% chance the election is decided by >1000 but <4000 votes, and the next $900M is worth it if there’s a 9% chance the election is decided by >4000 but <14000 votes. IMO the first two probably pass and the last one probably doesn’t, but idk.
I think if you think there’s a major difference between the candidates, you might put a value on the election in the billions—let’s say $10B for the sake of calculation.
You don’t need to think there’s a major difference between the candidates to conclude that the election of one candidate adds billions in value. The size of the US discretionary budget over the next four years is roughly three orders of magnitude your $10B figure, and a president can have an impact of the sort EAs care about in ways that go beyond influencing the budget, such as regulating AI, setting immigration policy, eroding government institutions and waging war.
Yes, but it’s kind of incoherent to talk about the dollar value of something without having a budget and an opportunity cost; it has to be your willingness-to-pay, not some dollar value in the abstract. Like, it’s not the case that the EA funding community would pay $500B even for huge wins like malaria eradication, end to factory farming, robust AI alignment solution, etc, because it’s impossible: we don’t have $500B.
And I haven’t thought about this much but it seems like we also wouldn’t pay, say, $500M for a 1-in-1000 chance for a “$500B win” because unless you’re defining “$500B win” with respect to your actual willingness-to-pay, you might wind up with many opportunities to take these kinds of moonshots and quickly run out of money. The dollar size of the win still has to ultimately account for your budget.
I think the core issue is that the lottery wins you government dollars, which you can’t actually spend freely. Government dollars are simply worth less, to Pablo, than Pablo’s personal dollars. One way to see this is that if Pablo could spend the government dollars on the other moonshot opportunities, then it would be fine that he’s losing his own money.
So we should stipulate that after calculating abstract dollar values, you have to convert them, by some exchange rate, to personal dollars. The exchange rate simply depends on how much better the opportunities are for personal spending, versus spending government money.
The fact that opportunities can get larger than your budget size seems not to be the core issue for the reason that you mention—that at realistic sizes of opportunity, it is possible to instead buy a lottery for a chance at the opportunity instead.
Yeah I roll to disbelieve too. One of my quantitative takeaways from Andrew Gelman’s modelling of the 2020 elections was that very few states (4/50, in particular New Hampshire, Pennsylvania, Wisconsin, and Michigan) were modelled as close enough that p(one vote changes outcome) > 1 in 10 million; New Hampshire tops the list at 1 in 8M. Optimistically assuming $100 per voter that’s still nearly a billion dollars at the very low end; a more realistic estimate would probably be ~1 OOM higher. Probably some sort of nonlinearity kicks in at this scale, or the most cost-effective tactics to sway voters cap out at relatively low levels for whatever reason?
On the flip side, I’m reminded of Scott’s essay Too much dark money in almonds? which provides an intuition pump for why it might be the case that it’s not as expensive as you may expect to swing the election:
Everyone always talks about how much money there is in politics. This is the wrong framing. The right framing is Ansolabehere et al’s: why is there so little money in politics? But Ansolabehere focuses on elections, and the mystery is wider than that. …
(in case you’re keeping track: all donations to all candidates, all lobbying, all think tanks, all advocacy organizations, the Washington Post, Vox, Mic, Mashable, Gawker, and Tumblr, combined, are still worth a little bit less than the almond industry. And Musk could buy them all.) …
In this model, the difference between politics and almonds is that if you spend $2 on almonds, you get $2 worth of almonds. In politics, if you spend $2 on Bernie Sanders, you get nothing, unless millions of other people also spend their $2 on him. People are great at spending money on direct consumption goods, and terrible at spending money on coordination problems.
(I don’t really have an opinion either way on whether more or less money should be spent on this)
I don’t think Gelman’s models are correct here. But even if they were, the numbers definitely don’t scale linearly. The vote margin ex post in the last 6 elections were all under 1M, the most recent 2 elections were under 100k. You’ll need pretty implausible assumptions (or really bad targetting) before you can fit an expectation of 10M ex ante votes to the observed ex post distribution.
This is my biggest confusion as well.
If you take:
along with:
You get that the entire election outcome can be purchased for ~$13M - $600M.
But I’m assuming it isn’t actually isn’t that cheap to swing the election?
Well, it implies you could change the election with those amounts if you knew exactly how close the election would be in each state and spent optimally. But If you figure the estimates are off by an OOM, and half of your spending goes to states that turn out not to be useful (which matches a ~30 min analysis I did a few months ago), and you have significant diminishing returns such that $10M-$100M is 3x less impactful than the first $10M and $100M-$1B is another 10x less impactful, you still get:
First $10M is ~$10k per key vote = 1,000 votes (enough to swing 2000)
Next $90M is ~$30k per key vote = 3,000 votes
Next $900M is ~$90k per key vote = 10,000 votes
I think if you think there’s a major difference between the candidates, you might put a value on the election in the billions—let’s say $10B for the sake of calculation; so the first $10M would be worth it if there’s a 0.1% chance the election is decided by <1000 votes (which of course happened 6 elections ago!), the next $90M is worth it if there’s a 0.9% chance the election is decided by >1000 but <4000 votes, and the next $900M is worth it if there’s a 9% chance the election is decided by >4000 but <14000 votes. IMO the first two probably pass and the last one probably doesn’t, but idk.
You don’t need to think there’s a major difference between the candidates to conclude that the election of one candidate adds billions in value. The size of the US discretionary budget over the next four years is roughly three orders of magnitude your $10B figure, and a president can have an impact of the sort EAs care about in ways that go beyond influencing the budget, such as regulating AI, setting immigration policy, eroding government institutions and waging war.
Yes, but it’s kind of incoherent to talk about the dollar value of something without having a budget and an opportunity cost; it has to be your willingness-to-pay, not some dollar value in the abstract. Like, it’s not the case that the EA funding community would pay $500B even for huge wins like malaria eradication, end to factory farming, robust AI alignment solution, etc, because it’s impossible: we don’t have $500B.
And I haven’t thought about this much but it seems like we also wouldn’t pay, say, $500M for a 1-in-1000 chance for a “$500B win” because unless you’re defining “$500B win” with respect to your actual willingness-to-pay, you might wind up with many opportunities to take these kinds of moonshots and quickly run out of money. The dollar size of the win still has to ultimately account for your budget.
I think the core issue is that the lottery wins you government dollars, which you can’t actually spend freely. Government dollars are simply worth less, to Pablo, than Pablo’s personal dollars. One way to see this is that if Pablo could spend the government dollars on the other moonshot opportunities, then it would be fine that he’s losing his own money.
So we should stipulate that after calculating abstract dollar values, you have to convert them, by some exchange rate, to personal dollars. The exchange rate simply depends on how much better the opportunities are for personal spending, versus spending government money.
The fact that opportunities can get larger than your budget size seems not to be the core issue for the reason that you mention—that at realistic sizes of opportunity, it is possible to instead buy a lottery for a chance at the opportunity instead.
Yeah I roll to disbelieve too. One of my quantitative takeaways from Andrew Gelman’s modelling of the 2020 elections was that very few states (4/50, in particular New Hampshire, Pennsylvania, Wisconsin, and Michigan) were modelled as close enough that p(one vote changes outcome) > 1 in 10 million; New Hampshire tops the list at 1 in 8M. Optimistically assuming $100 per voter that’s still nearly a billion dollars at the very low end; a more realistic estimate would probably be ~1 OOM higher. Probably some sort of nonlinearity kicks in at this scale, or the most cost-effective tactics to sway voters cap out at relatively low levels for whatever reason?
On the flip side, I’m reminded of Scott’s essay Too much dark money in almonds? which provides an intuition pump for why it might be the case that it’s not as expensive as you may expect to swing the election:
(I don’t really have an opinion either way on whether more or less money should be spent on this)
I don’t think Gelman’s models are correct here. But even if they were, the numbers definitely don’t scale linearly. The vote margin ex post in the last 6 elections were all under 1M, the most recent 2 elections were under 100k. You’ll need pretty implausible assumptions (or really bad targetting) before you can fit an expectation of 10M ex ante votes to the observed ex post distribution.