Electoral predictors of polling errors

Abstract

To understand when polls are accurate and when they fail, we adopt a Bayesian hierarchical modeling approach that separates poll bias and variance at the election level, and links error components to a broad range of election features including mobi- lization, candidacies, polarization, and electoral conduct. An empirical study of 9,298 pre-election polls across the 367 U.S. Senate elections, 1990-2022, reveals an over- all trend toward smaller but more uniform errors over time, a negative association between poll variance and mobilization and polarization, and a tendency to underes- timate more ideologically extreme Republican candidates. Moreover, Republican poll bias has a modestly positive link with the level of state democracy. Contrary to the- oretical expectations, we find little evidence that female or minority candidates are overestimated in polls. While large parts of the variance remain unaccounted for, the empirical approach is promising and easily extended to include other potential error sources.

Content

Supplementary material

Supplementary materials
A) Number of polls over the legislative period , B) Prior specificatioon, C) Minority status based on facial characteristics and name, D) Results by election cycle

Comments

Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting and Discussion Policy [opens in a new tab] – please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .