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Models are backtested against the historical record where hundreds or thousands of elections (federal, state and local) can be used as training data. For examp

by awb 6y ago

Models are backtested against the historical record where hundreds or thousands of elections (federal, state and local) can be used as training data. For example, a weighted average of polls has Biden up ~5% in PA. In state-wide elections, I wouldn't be surprised if candidates with that sized lead in PA (and states with similar size and socioeconomic demographics) end up winning about 85% of the time, which is what the 538 model has Biden's chances at in PA. That 15% uncertainty accounts for the bias you describe. If polling was perfect and there was no bias, a ~5% polling lead (and exceeding the margin of error) would be a 100% guaranteed victory. It would be great to see Taleb's forecast of federal and state elections so he has "skin in the game" as he likes to say. Assume you get points based on your % confidence, so if you predict there's a 55% chance of a particular outcome and you're right you get 55pts, and if you're wrong you lose 55pts. If Taleb pegs every race at 50/50 or 55/45 because you "can't predict elections", I doubt his score will be higher than Silver's. You'll end up with silly predictions like 40% chance of Trump winning Washington DC or 30% chance of Biden winning Wyoming, when in reality each have less than 1% chance of doing so. When you make reasonable, weighted predictions based on state polling, you see that Biden has leads outside the margin of error in states totaling 270 EV. So, the 10% chance Silver gives Trump is saying, hey there's a chance that the polls could be extremely biased in all 7 swing states in Trump's favor. But, if Trump loses even 1 of those swing states, there are so many safe D electoral votes that Biden will win.

nwienert 6y ago
You totally ignored the point. Overfitting to previous results doesn’t account for the fact that the facts on the ground are changing. I mean this year alone we have a once in a century pandemic, can you fit that to any other election?
- awb 6y ago
  That's why you test predictions. Silver says 10% is enough uncertainty, Taleb says it's not. From the article: "Premise 1: If you give a probability, you must be willing to wager on it". Unless they're willing to publish and make a friendly bet on their predictions, it's just bloviating. Every day/year/election is unique, but only to a certain magnitude. Some elections have had active wars, some health crises, some criminal scandals, some terrorist attacks, etc. In the end, the polls attempt to account for those uncertainties and historically that's been a much better predictor than a coin flip. For example, Washington DC has never voted Republican since it won electoral votes in 1962. Polls have Biden winning 80-90% of the vote there. Even Taleb would agree there's a near 100% chance of Biden winning there, pandemic or not. Silver's methodology is just extrapolating that out to each state. When it gets to some tipping point states it's closer to 60/40 Biden or 70/30. If Taleb wants to create his own forecast, it would be interesting to track it's performance over time. I have a hard time believing that model closer to a coin-flip is going to outperform weighted polling data and historical precedent over multiple predictions.
  - nwienert 6y ago
    Seems like the polls were systematically dramatically off, again.
    - awb 6y ago
      Right, but the original point was that Biden's lead was likely large enough in enough swing states to overcome a 2016-style polling bias, which looks like has occurred in some states. That's why it was a 10% chance for Trump, because he had to not just have a large polling error go his way, but also in enough swing states to total 270. A landslide Biden victory was as probable as a narrow Biden victory. And both were more likely than a narrow Trump victory.
      - nwienert 6y ago
        But that’s simply not true. Because Florida and Texas alone were so far off, 10% odds was definitely “way” wrong. Nate’s model predicted that if Florida went Trump the odds were at 33% or so. Texas moreso, etc. Since Florida went incredibly strongly Trump, we can say with certainty he was completely wrong on the 10% chance. That’s the point: he was way overconfident his past model would fit, it should have been closer to a slightly advantage, which would read something like 60/40 at best.
        awb 6y ago
        > Since Florida went incredibly strongly Trump, we can say with certainty he was completely wrong on the 10% chance. The model generated 40k scenarios, and the scenario you're describing is one of them. The most extreme scenarios have Trump winning all swing states by a few %, which doesn't look likely. So what's playing out is not wildly outside the predictions by any means. In other words, if a 10% chance happens, it doesn't mean the 10% prediction was wrong. The only way to prove a prediction was wrong is to bet against it over time with your own predictions. As Silver has shown there's a huge appetite for election / sports predictions. Anyone able to beat him over time would have enormous income potential. For example, if you thought Trump had at least a 40% chance to win, you'd have a great betting opportunity in the market that had Trump in the 25-33% range. You could have bought in then and sold when Trump's chance peaked at about 50-60%. If you arbitrage those mistakes you've identified in the market, overtime you could become very wealthy. Until then, it's just pundits pontificating after the results are known without putting any money or reputation on the line beforehand, similar to a casual sports fan late in the 4th quarter: "of course the 49ers were going to blow their lead -- I just knew it!"

by awb 6y ago

nwienert 6y ago

You totally ignored the point. Overfitting to previous results doesn’t account for the fact that the facts on the ground are changing. I mean this year alone we have a once in a century pandemic, can you fit that to any other election?

awb 6y ago
That's why you test predictions. Silver says 10% is enough uncertainty, Taleb says it's not. From the article: "Premise 1: If you give a probability, you must be willing to wager on it". Unless they're willing to publish and make a friendly bet on their predictions, it's just bloviating. Every day/year/election is unique, but only to a certain magnitude. Some elections have had active wars, some health crises, some criminal scandals, some terrorist attacks, etc. In the end, the polls attempt to account for those uncertainties and historically that's been a much better predictor than a coin flip. For example, Washington DC has never voted Republican since it won electoral votes in 1962. Polls have Biden winning 80-90% of the vote there. Even Taleb would agree there's a near 100% chance of Biden winning there, pandemic or not. Silver's methodology is just extrapolating that out to each state. When it gets to some tipping point states it's closer to 60/40 Biden or 70/30. If Taleb wants to create his own forecast, it would be interesting to track it's performance over time. I have a hard time believing that model closer to a coin-flip is going to outperform weighted polling data and historical precedent over multiple predictions.
- nwienert 6y ago
  Seems like the polls were systematically dramatically off, again.
  - awb 6y ago
    Right, but the original point was that Biden's lead was likely large enough in enough swing states to overcome a 2016-style polling bias, which looks like has occurred in some states. That's why it was a 10% chance for Trump, because he had to not just have a large polling error go his way, but also in enough swing states to total 270. A landslide Biden victory was as probable as a narrow Biden victory. And both were more likely than a narrow Trump victory.
    - nwienert 6y ago
      But that’s simply not true. Because Florida and Texas alone were so far off, 10% odds was definitely “way” wrong. Nate’s model predicted that if Florida went Trump the odds were at 33% or so. Texas moreso, etc. Since Florida went incredibly strongly Trump, we can say with certainty he was completely wrong on the 10% chance. That’s the point: he was way overconfident his past model would fit, it should have been closer to a slightly advantage, which would read something like 60/40 at best.
      - awb 6y ago
        > Since Florida went incredibly strongly Trump, we can say with certainty he was completely wrong on the 10% chance. The model generated 40k scenarios, and the scenario you're describing is one of them. The most extreme scenarios have Trump winning all swing states by a few %, which doesn't look likely. So what's playing out is not wildly outside the predictions by any means. In other words, if a 10% chance happens, it doesn't mean the 10% prediction was wrong. The only way to prove a prediction was wrong is to bet against it over time with your own predictions. As Silver has shown there's a huge appetite for election / sports predictions. Anyone able to beat him over time would have enormous income potential. For example, if you thought Trump had at least a 40% chance to win, you'd have a great betting opportunity in the market that had Trump in the 25-33% range. You could have bought in then and sold when Trump's chance peaked at about 50-60%. If you arbitrage those mistakes you've identified in the market, overtime you could become very wealthy. Until then, it's just pundits pontificating after the results are known without putting any money or reputation on the line beforehand, similar to a casual sports fan late in the 4th quarter: "of course the 49ers were going to blow their lead -- I just knew it!"