I learned from the reporting on the financial crisis there is no way to model your way out of bad data! https://twitter.com/jim_newell/status/1324078869025071105 …
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Its just messy.
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Yeah I tend to agree with you on this.
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Campaigns can use them (should be cautious about them anyway), they can be used to look for fraud (expected correlations etc.) or people who enjoy gambling as entertainment can treat them as entertainment. The rest, along with horse race coverage, not that helpful.
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Not to get all meta, but wasn't most of the polling in 2018 (and for that matter, outside upper-Midwest state polls in 2016) pretty decent? Now I want some data about the data.
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My recollection is that election night 2018 people thought the polls were wrong, but as the count rolled in over a few days, there was a blue wave that lined up pretty neatly with the predicted results.
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Models are a means of making raw data more useful, and can do so in provably true ways. They can be a useful tool for explaining probability and uncertainty. Maybe models a scapegoat for broader horserace obsession that, in some sense, they're working to make less irresponsible?
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This seems especially indisputable given their high profile failure in 2016, from which the models apparently learned absolutely nothing despite it being the most relevant and most recent data point. They failed in the same way, in the same places.
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Here's what I'm tossing about - is the data bad because of misinformation by voters, more limited sample selection, or (as I suspect here) "likely voters" who didn't get a ballot counted despite their best efforts?
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