The Economist-20241109期「United States」Campaign calculus: Fool me thrice
02 全文梳理
【Para1】大选“反转”👉今年美国总统选举中，特朗普让民调专家们大跌眼镜，他所获得的票数比民调显示的高。
【Para2-4】具体表现:
-para2 总体评价👉总体而言，民调正确反映出了选举的激烈程度，但仍然在预估特朗普支持者上出现了错误。
-para3 误差范围👉以之前的选举相比，本次民调虽出错但和实际票数的误差缩小。
-para4 核心难题👉本次民调的失误是全国性的，而且机构们已连续多次低估特朗普的影响力。
【Para5-7】改进方案：
-para5 调整权重👉在过去的选举周期中，由于部分群体不参加民调，专家们会通过调整权重的方法来增加这些群体的影响力。
-para6 调整结果👉16和20年的大选后，民调都对共和党的投票者进行了投票加权，这导致两党的预测差距已有缩小。
-para7 加权弊端👉加权能解决的问题是有限的，而且权重的设定还受主观影响。
【Para8】作者点评👉倘若不能解决样本代表性问题，民调将很难反应真实的投票风向。
03 原文阅读 571words
Campaign calculus: Fool me thrice
A small but stubborn error affected polls across the board
Campaign calculus: Fool me thrice
A small but stubborn error affected polls across the board
[5] In past election cycles, pollsters have tweaked survey “weights” to make their samples of voters more representative. Although polls aim to sample the population randomly, in practice they often systematically miss certain groups. Weights are used to increase the influence of under-represented respondents. This has been especially true in recent years as response rates have plummeted.
[6] After the 2016 election, when surveys systematically missed voters without college degrees and therefore underestimated support for Mr Trump, pollsters began accounting for respondents' education levels. And after 2020, in an effort to ensure that Republican voters were represented, more pollsters began weighting their samples by respondents' party registration and self-reported voting history. This caused the range of poll outcomes to narrow (weighting reduces the variance of survey results), with many pollsters finding similar results in key states and nationwide.
[7] If there is a lesson from this year's election, it could be that there is a limit to what weighting can solve. Although pollsters may artificially make a sample “representative” on the surface, if they do not address the root causes of differential response rates, they will not solve the underlying problem. They also introduce many subjective decisions, which can be worth almost eight points of margin in any given poll.
[8] A pollster which gets those decisions right appears to be prophetic. But with limited transparency before the election, it is hard to know which set of assumptions each has made, and whether they are the correct ones. To their credit, the pollsters get together to conduct comprehensive post-election reviews. This year's may be revealing. Still, without a breakthrough technology that can boost the representativeness of survey samples, weighting alone is unlikely to solve pollsters' difficulty in getting a reliable read on what Trump voters are thinking. ■
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