Republicans have recently become more likely to take part in pollsters' surveys, inflating Donald Trump's approval ratings
day since he took office, Donald Trump has had a lower job-approval rating than almost every other modern president at the same point in their tenure. But over the past two weeks the polls have finally been giving Mr Trump some good news. According to an average of public polling data calculated by FiveThirtyEight, a data-journalism website, he is more popular than he has been since March 2017, two months after he took office. Thecalled it Mr Trump’s “best week” yet in office.
These positive appraisals have overlooked a crucial fact about the methods of conducting opinion polls in America. Because the people who take part in surveys are often not representative of the population as a whole, pollsters use a statistical procedure called “weighting”, which adjusts the findings to meet certain demographic targets.
But even after correcting for demographic biases, pollsters’ data can still be unrepresentative. They may have the right shares of Latino voters and boomers, but nevertheless have too many Republicans or Democrats. This concern is pronounced when an event causes especially good, or bad, news for a political party. At such times surveys can suddenly be swamped with partisans who are eager to voice their love, or hate, for the president.
In the wake of Mr Trump’s acquittal in the Senate, pollsters suspect that such a bias could be affecting polls. Courtney Kennedy, the director for survey research at the Pew Research Centre, says that there is a “strong possibility” that the recent uptick in Mr Trump’s ratings has a wave of optimistic Republicans as its source.
Hence pollsters who do not adjust for partisan bias have picked up a recent—and mostly phantom—swing in Mr Trump’s favour. Yet Ms Kennedy is quick to say that weighting is not a magic wand for ensuring high-quality results. A recent Pew report found that online surveys, in particular, can also be unduly influenced by so-called bogus participants who could be causing even more errors in pollsters’ measurements by submitting nonsensical, and disproportionately positive, responses.
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