| Comment | should rather say ... —> should say ... instead Sorry if I was slow on the uptake, Nathan, but thanks for the explanation. Yes, most analysts seem to think the U. S. House is not likely to slip from Democratic control. It's the Senate that is a big question and a very close contest. A few more articles, one on Texas and two on (the dangers of putting too much credence in) forecasting. My own sense is that it's going to be a very tight race, still mostly within the margin of error in most states that matter, so that it would not be at all surprising if Trump could still win. But I would be very happy to be proved wrong if Biden could take either Florida or Texas, both of which probably have enough early voting and allow enough election-day counting to have a sense of a result sometime tomorrow night, unlike some of the Midwestern swing states that have longer mail-in deadlines. _______________ Democrats Dare to Get Their Hopes Up Again in Texas
To win the state House they’ll need to clean up in the suburbs around Dallas and Houston. ...
Democrats have two high hopes for Texas on Tuesday. First, deliver its 38 electoral votes to Joe Biden. Second, win control of the state House by flipping at least nine Republican-held seats. With Republicans overwhelmed in Texas’ cities and struggling in the suburbs, neither development is unthinkable.
If Democrats are wary, however, it is because they have seen their high hopes for Texas dashed over and over. ... A Democratic victory in a 2020 special election for a suburban Houston U.S. House seat was going to announce a coming blue shift in the state—until the Republican won 58% to 42%.
Before Covid-19, many national Democrats were swearing off Texas, which they had come to regard as a bottomless pit into which donors in the other 49 states shovel money in return for nothing but humiliation. But this October they have dared to get their hopes up again. ...
A Biden victory in Texas would be a dispiriting blow for Republicans, but it is possible: The FiveThirtyEight polling average has had President Trump’s lead at 1.2%, and Quinnipiac has the two candidates tied at 47%.
Incredible as it may sound to outsiders, Democrats may have a better chance of winning the presidential election in Texas than they do of winning the state House. That’s because Texans vote more heavily Republican in state and local races than they do in presidential races: Mr. Trump underperformed Republican congressional candidates in Texas by 5 points in 2016. The president won only 52% in Texas, against 58% in neighboring Louisiana, 61% in Arkansas and 65% in Oklahoma. ...
One of the Karl Roves of the world, Karl Rove, concedes that Republicans have immediate and long-term challenges in Texas. “We’ve got to do better with the Latino community, but the big problem for Republicans in Texas isn’t Latinos—it’s urbanization,” says the former aide to President George W. Bush and regular contributor to these pages. Six of the 25 largest U.S. cities are in Texas; Dallas and Houston are the fourth- and fifth-largest metropolitan areas in the country, respectively. And it is in and around these cities that Republicans are falling behind. Houston and San Antonio have been strongly Democratic for a generation, and their suburbs are trending that way, too. When Fort Worth went for Mr. O’Rourke over Mr. Cruz, that left the Panhandle outpost of Lubbock, population 255,000, as the largest reliably Republican city in the state.https://www.wsj.com/articles/democrats-dare-t...Why You Can’t Rely on Election Forecasts
Voting models are not as scientific or certain as they may seem.
By Zeynep Tufekci ...
There are two broad ways to model an event: using “fundamentals” — mechanisms that can affect the event — and probabilities — measurements like polls. For elections, fundamentals would be historically informed lessons like, “a better economy favors incumbents.” With polls, there is no theory about why they are the way they are. We just use the numbers they produce.
Electoral forecast modelers run simulations of an election based on various inputs — including state and national polls, polling on issues and information about the economy and the national situation. If they ran, say, 1,000 different simulations with various permutations of those inputs, and if Joe Biden got 270 electoral votes in 800 of them, the forecast would be that Mr. Biden has an 80 percent chance of winning the election.
This is where weather and electoral forecasts start to differ. For weather, we have fundamentals — advanced science on how atmospheric dynamics work — and years of detailed, day-by-day, even hour-by-hour data from a vast number of observation stations. For elections, we simply do not have anything near that kind of knowledge or data. While we have some theories on what influences voters, we have no fine-grained understanding of why people vote the way they do, and what polling data we have is relatively sparse.
Consequently, most electoral forecasts that are updated daily — like those from FiveThirtyEight or The Economist — rely heavily on current polls and those of past elections, but also allow fundamentals to have some influence. Since many models use polls from the beginning of the modern primary era in 1972, there are a mere 12 examples of past presidential elections with dependable polling data. That means there are only 12 chances to test assumptions and outcomes, though it’s unclear what in practice that would involve.
A thornier problem is that unlike weather events, presidential elections are not genuine “repeat” events. Facebook didn’t play a major role in elections until probably 2012. Twitter, without which Mr. Trump thinks he might not have won, wasn’t even founded until 2006. How much does an election in 1972, conducted when a few broadcast channels dominated the public sphere, tell us about what might happen in 2020? ...
In its final forecast in 2016, FiveThirtyEight gave Hillary Clinton a 71.4 percent chance of victory. (The digit after the decimal providing an aura of faux precision, as if we could distinguish 71.4 percent from 71.5 percent.) All that figure really said was that Mrs. Clinton had a roughly one-in-three chance of losing, something that did not get across to most people who saw a big number. Most sites gave an even bigger number, with The New York Times predicting Mrs. Clinton had an 85 percent chance of winning on the day of the vote. ...
One key problem in 2016 was the assumptions pollsters made when modeling the electorate — the people who would actually show up to vote. Pollsters were a little off in estimating the educational level of the electorate, especially in the Midwest. What’s more, people who settled on a preference late were a bit more prone to vote for Mr. Trump, and his supporters were a bit more likely to turn out than the models assumed. Even small shifts like that matter greatly; if it’s happening in one state, it’s probably happening in many similar states.
In 2020, it’s even harder to rely on polls or previous elections: On top of all the existing problems with surveys in an age of cellphones, push polls and mistrust, we’re in the middle of a pandemic. ... These are big unknowns that add great uncertainty to models, especially given the winner-takes-all setup in the Electoral College, where winning a state by as little as one-fourth of 1 percent can deliver all its electoral votes.
There’s an even more fundamental point to consider about election forecasts and how they differ from weather forecasting. If I read that there is a 20 percent chance of rain and do not take an umbrella, the odds of rain coming down don’t change. Electoral modeling, by contrast, actively affects the way people behave.
In 2016, for example, a letter from the F.B.I. director James Comey telling Congress he had reopened an investigation into Mrs. Clinton’s emails shook up the dynamics of the race with just days left in the campaign. Mr. Comey later acknowledged that his assumption that Mrs. Clinton was going to win was a factor in his decision to send the letter.
Similarly, did Facebook, battered by conservatives before the 2016 election, take a hands-off approach to the proliferation of misinformation on its platform, thinking that Mrs. Clinton’s odds were so favorable that such misinformation made little difference? Did the Obama administration hold off on making public all it knew about Russian meddling, thinking it was better to wait until after Mrs. Clinton’s assumed win, as has been reported?
Indeed, in one study,
( https://www.journals.uchicago.edu/doi/abs/10.... )
researchers found that being exposed to a forecasting prediction “increases certainty about an election’s outcome, confuses many, and decreases turnout.” Did many people think like Edward Snowden, who famously tweeted to millions of followers 18 days before Election Day, “There may never be a safer election in which to vote for a third option,” appending a New York Times forecast claiming that Hillary Clinton had a 93 percent chance of victory to his tweet? Did more Clinton voters stay home, thinking their vote wasn’t necessary? Did more people on the fence feel like casting what they thought would be a protest vote for Donald Trump? We’ll never know. ...
... given all the uncertainty, misunderstanding and fragility of electoral forecasts, I’m not sure there is a meaningful difference between, say, a 20 percent and a 40 percent chance of winning. That’s another way of saying these forecasts aren’t that useful, and may even be harmful if people take them too seriously.
Instead of refreshing the page to update predictions, people should do the only thing that actually affects the outcome: vote, donate and organize. Everything else is within the margin of error.https://www.nytimes.com/2020/11/01/opinion/el...A Math Whiz on How to Stop Stressing About Election Forecasts
An interview with the mathematician Jordan Ellenberg about politics, election forecasting, and how to think about the future like a pro ...
... the smartest modelers out there say Biden has roughly a 90 percent chance of winning the presidential election. If Biden wins, it won’t necessarily mean the forecasts were correct. Maybe his “real” odds were more likely 50 percent (or 99.9 percent). If Trump loses, it won’t necessarily mean his 10 percent odds were wrong, either. One-in-10 events happen all the time. Just now, I flipped a coin three times, and it landed heads-heads-tails. The odds of that exact sequence: 12.5 percent. Unlikely things happen so constantly that you could say reality is mostly one unlikely thing after another. ...
I wanted to know if America’s forecast addiction was understandable, paradoxical, or pathological. So I called Jordan Ellenberg, a mathematician and University of Wisconsin professor, who wrote a best-selling book about thinking mathematically. ...
(http://www.jordanellenberg.com/how-not-to-be-... ) ...
In many contexts, we overlook small odds. FiveThirtyEight gives Trump a 3 percent chance of winning New Mexico. Most people are going to look at that and say: “Okay, Trump isn’t going to win New Mexico.” I would not complain if you said that.
But now think about COVID. If you’re a 65-year-old person, you have a 99 percent chance of survival if you get this virus. The odds of death are smaller than the odds of Trump winning New Mexico, which I just said you can maybe ignore. But a 1 percent chance of your own death in two weeks? That’s a completely different risk. People go out of their way to avoid things that give them a one-in-100 chance of dying. When they don’t, we call them idiots. ...
A good mental-health question to ask yourself is: What am I actually gaining from trying to figure this out now? None of us sitting at home is going to decide the election. The meaningful actions we’re going to take in support of our preferred candidate at every level have mostly been taken, or decided. So what are we gaining? We’re all about to find out the answer. Our epistemic situation when we know the outcome of the election will be the exact same no matter how hard we think about it right now. Our stress affects nothing.https://www.theatlantic.com/ideas/archive/202... |
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