Abstract

We present a polling strategy to predict and analyze runoff elections using the 2017 French presidential race as an empirical case. This strategy employs rejective probability sampling to identify a small sample of polling stations that is balanced with respect to past election results. We then survey the voters’ candidate evaluations in first-round exit polls. We poststratify the voter sample to first-round election returns to account for nonresponse and coverage issues, and impute missing candidate evaluations to emulate campaign learning. Next, the votes for eliminated competitors are redistributed according to their supporters’ lower-order preferences. Finally, the predictions are validated against official results and other polls. We end with a discussion of the advantages and limitations of this approach.

中文翻译：

---

如何对径流选举进行投票

摘要

我们以2017年法国总统大选为例，提出了一种预测和分析径流选举的投票策略。该策略采用拒绝概率抽样来确定少量投票站样本，这些样本相对于过去的选举结果是平衡的。然后，我们在第一轮退出民意调查中调查选民的候选人评价。我们将选民样本分层到第一轮选举中，以解决无人回应和报道问题，并估算缺少的候选人评估以模拟竞选活动学习。接下来，将根据支持者的低阶偏好重新分配被淘汰竞争对手的选票。最后，根据官方结果和其他民意测验对预测进行了验证。我们最后讨论了这种方法的优点和局限性。