Predicting elections: Experts, polls, and fundamentals
Journal Title: Judgment and Decision Making - Year 2018, Vol 13, Issue 4
Abstract
This study analyzes the relative accuracy of experts, polls, and the so-called ‘fundamentals’ in predicting the popular vote in the four U.S. presidential elections from 2004 to 2016. Although the majority (62%) of 452 expert forecasts correctly predicted the directional error of polls, the typical expert’s vote share forecast was 7% (of the error) less accurate than a simple polling average from the same day. The results further suggest that experts follow the polls and do not sufficiently harness information incorporated in the fundamentals. Combining expert forecasts and polls with a fundamentals-based reference class forecast reduced the error of experts and polls by 24% and 19%, respectively. The findings demonstrate the benefits of combining forecasts and the effectiveness of taking the outside view for debiasing expert judgment.
Authors and Affiliations
Andreas Graefe
Keywords
Related Articles
- EP ID EP678365
- DOI -
- Views 175
- Downloads 0
Reducing the impact bias in judgments of post-decisional affect: Distraction or task interference?
People overestimate their affective reactions to future events and decisions — a phenomenon that has been termed “impact bias.” Evidence suggests that completing a diary detailing events contemporaneous with the focal on...
The impact of time limitation: Insights from a queueing experiment
We experimentally explore the effects of time limitation on decision making. Under different time allowance conditions, subjects are presented with a queueing situation and asked to join one of the two given queues. The...
The retrospective gambler’s fallacy: Unlikely events, constructing the past, and multiple universes
The gambler’s fallacy (Tune, 1964) refers to the belief that a streak is more likely to end than chance would dictate. In three studies, participants exhibited a retrospective gambler’s fallacy (RGF) in which an event th...
From group diffusion to ratio bias: Effects of denominator and numerator salience on intuitive risk and likelihood judgments
The group-diffusion effect is the tendency for people to judge themselves to be less likely to experience a negative outcome as the total number of people exposed to the threat increases — even when the probability of th...
Attribute framing affects the perceived fairness of health care allocation principles
Health care resource allocation is a central moral issue in health policy, and opinions about it have been studied extensively. Allocation situations have typically been described and presented in a positive manner (i.e....