Citizen Forecasting 2020

A State-by-State Experiment

Dados Bibliográficos

ID6101193
AutoresAndreas Erwin Murr (0000-0002-9536-0118, University of Warwick), Michael S Lewis-Beck (0000-0003-0301-5497, University of Iowa)
Ano2021
Volume54
Fascículo1
Páginas91-95
Data de publicação2021-01-01
Open AccessSim
TipoARTICLE
PeriódicoPS Political Science & Politics (JOURNAL)
Identificadores do periódicoISSN: 1049-0965 • E-ISSN: 1537-5935
EditoraCambridge University Press (CUP) (PUBLISHER)
DOI10.1017/s1049096520001456
OpenAlexW3119703394
IdiomaEN
Citações recebidas4
Referências citadas12

The leading approaches to scientific election forecasting in the United States consist of structural models, prediction markets and opinion polling. With respect to the last, by far the dominant mode relies on vote intention polling, e.g., “If the election were held tomorrow, who would you vote for?” However, there exists an abiding opinion polling strategy that shows a good deal of promise—citizen forecasting. That is, rather than query on vote intention, query on vote expectation, e.g., “Who do you think will win the upcoming election?” This approach has been pursued most extensively in the United Kingdom (Murr 2016) and the United States (LewisBeck and Tien 1999). Recent performance evaluations have shown that in the United Kingdom vote expectations clearly offer more predictive accuracy than vote intentions (Murr et al. forthcoming) and that in the United States vote expectations appear to be superior to an array of rival forecasting tools (Graefe 2014). However, the timing of the data collection has forced most of the studies using citizen forecasts to forecast elections ex post, i.e., after they occurred. Indeed, to date, there are only two ex ante citizen forecasting papers to have appeared before a national election (Lewis-Beck and Stegmaier 2011; Murr 2016). Both these efforts forecasted British General Elections, with Murr (2016) relatively most accurate among 12 academic forecasts (Fisher and Lewis-Beck 2016). \n \nWith respect to the United States, the case at hand, none of the work has been ex ante and all studies have focused on the national level, with the exception of a lone study carried out at the state level (Murr, 2015). The latter point seems critical, since the final selection of the president takes place in the Electoral College. The citizen forecasting research here stands unique, being ex ante and focusing on the states. Utilizing survey questions on Amazon.com’s Mechanical Turk (MTurk), administered in July, we render forecasts for the November 2020 presidential contest. This experiment, which has been conducted before-the-fact and looks at the states, provides a strong test of the quality of citizen forecasting in this American election

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