Skip to main content
SearchLogin or Signup

Towards Principled Unskewing: Viewing 2020 Election Polls Through a Corrective Lens from 2016

Published onNov 03, 2020
Towards Principled Unskewing: Viewing 2020 Election Polls Through a Corrective Lens from 2016
·
history

You're viewing an older Release (#1) of this Pub.

  • This Release (#1) was created on Oct 27, 2020 ()
  • The latest Release (#2) was created on Nov 03, 2020 ().

Abstract

We apply the concept of the data defect index (Meng, 2018) to study the potential impact of systematic errors on the 2020 pre-election polls in twelve Presidential battleground states. We investigate the impact under the hypothetical scenarios that (1) the magnitude of the underlying non-response bias correlated with supporting Donald Trump is similar to that of the 2016 polls, (2) the pollsters’ ability to correct systematic errors via weighting has not improved significantly, and (3) turnout levels remain similar to 2016. Because survey weights are crucial for our investigations but are often not released, we adopt two approximate methods under different modeling assumptions. Under these scenarios, which may be far from reality, our models shift Trump’s estimated two-party vote share by a percentage point in his favor in the median battleground state, and increases twofold the uncertainty around the vote share estimate.


Just Accepted - Preview

10/27/20: To preview this content, click below for the Just Accepted version of the article. This peer-reviewed version has been accepted for its content and is currently being copyedited to conform with HDSR’s style and formatting requirements.

Comments
0
comment

No comments here