Forecasting elections with mere recognition from small, lousy samples: A comparison of collective recognition, wisdom of crowds, and representative polls

Details

Serval ID
serval:BIB_908B40B01393
Type
Article: article from journal or magazin.
Collection
Publications
Title
Forecasting elections with mere recognition from small, lousy samples: A comparison of collective recognition, wisdom of crowds, and representative polls
Journal
Judgment and Decision Making
Author(s)
Gaissmaier W., Marewski J. N.
ISSN
1930-2975
Publication state
Published
Issued date
02/2011
Peer-reviewed
Oui
Volume
6
Number
1
Pages
73-88
Language
english
Abstract
We investigated the extent to which the human capacity for recognition helps to forecast political elections: We compared naive recognition-based election forecasts computed from convenience samples of citizens' recognition of party names to (i) standard polling forecasts computed from representative samples of citizens' voting intentions, and to (ii) simple-and typically very accurate-wisdom-of-crowds-forecasts computed from the same convenience samples of citizens' aggregated hunches about election results. Results from four major German elections show that mere recognition of party names forecast the parties' electoral success fairly well. Recognition-based forecasts were most competitive with the other models when forecasting the smaller parties' success and for small sample sizes. However, wisdom-of-crowds-forecasts outperformed recognition-based forecasts in most cases. It seems that wisdom-of-crowds-forecasts are able to draw on the benefits of recognition while at the same time avoiding its downsides, such as lack of discrimination among very famous parties or recognition caused by factors unrelated to electoral success. Yet it seems that a simple extension of the recognition-based forecasts-asking people what proportion of the population would recognize a party instead of whether they themselves recognize it-is also able to eliminate these downsides.
Keywords
Political elections, Recognition, Forecasting, Heuristics, Wisdom of crowds
Web of science
Create date
14/10/2011 11:50
Last modification date
20/08/2019 14:53
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