From unherd.com:
Far from learning from the mistakes of 2016, the polling industry seemed to have got things worse. Whether conducted by private or public firms, at the national or local, presidential or senatorial, levels, polls were off by wide margins. The Five Thirty-Eight final poll of polls put Biden ahead by 8.4 points, but the actual difference in popular vote is likely to be closer to 3-4 points. In some close state races, the error was even greater.
Why did they get it so wrong? Pollsters typically receive low response rates to calls, which leads them to undercount key demographics. To get around this, they typically weight for key categories like race, education or gender. If they get too few Latinos or whites without degrees, they adjust their numbers to match the actual electorate.
But most attitudes vary far more within a group like university graduates, than between graduates and non-graduates. So even if you have the correct share of graduates and non-graduates, you might be selecting the more liberal-minded among them. For example, in the 2019 American National Election Study pilot survey, education level predicts less than 1% of the variation in whether a white person voted for Trump in 2016. By contrast, their feelings towards illegal immigrants on a 0-100 thermometer predicts over 30% of the variation. Moreover, immigration views pick out Trump from Clinton voters better within the university-educated white population than among high school-educated whites. Unless pollsters weight for attitudes and psychology – which is tricky because these positions can be caused by candidate support – they miss much of the action.
Your assumption is wrong, that's why you're confused.
ReplyDeleteThe pollsters never intend to convey accurate information with their pre-election results. The goal is to encourage their allies and demoralize their opponents.
If they wanted truth, they are more than capable of doing so.