Philippe Mongrain

Université de Montreal

Département de science politique
Programme: PhD
Superviseur: Jean-François Godbout
Co-superviseur: Ruth Dassonneville
Début: 2017
Fin: 2022

Titre: Citizens as Election Forecasters

Most studies explain the quality of citizens' forecasts by the 'miracle of aggregation,' which states that errors in individuals' judgments tend to cancel out in the aggregate (assuming these errors are randomly distributed). However, for the aggregation principle to work, most citizens must have a better probability of guessing the outcome than they are of making an erroneous prediction. Research on individual-level correlates of forecasting abilities has been somewhat scant. Up until now, explanations of citizens' forecasting skills have taken the form of three models, that is (1) the Political Model, (2) the Contextual Model, and (3) the Contact Model. However, these models, which will be reviewed in the following section, either fail to offer significant explanations of citizens' forecasting abilities or suffer from a cruel lack of testing. Furthermore, alternative explanations have been largely ignored. Although cognitive styles, that is how people think and process information (e.g., how they embrace uncertainty or how they deal with conflicting viewpoints), have been shown to affect individuals' forecasting skills (e.g., Tetlock and Gardner 2015), psychological explanations are almost entirely left out of the voter expectations literature. The lack of adequate research is even deeper for institutional explanations: electoral rules and tradition of coalition agreements have the potential to make election outcomes less foreseeable. Unfortunately, to date, no study has looked at the impact of political institutions on voters' expectations. Citizens appear to be decent election forecasters. However, the reasons for this are still unclear, especially in light of the low political information levels among citizens in democratic countries and individuals' general tendency to overestimate the probability their preferred outcome will occur. Consequently, the proposed thesis is guided by one overarching question: What can explain an individual's ability to correctly forecast the outcome of an election?

Bourse d'excellence Joseph-Armand-Bombardier du Conseil de recherches en sciences humaines; Bourse de maîtrise en recherche du Fonds de recherche du Québec, Société et culture; Bourse de doctorat en recherche du Fonds de recherche du Québec, Société et culture; Bourse de doctorat du CRSH; Bourse Warren E. Miller

La prédiction des résultats électoraux au Canada : un modèle politico-économique sans sondage
Journal: Canadian Journal of Political Science / Revue canadienne de science politique
Volume: 52
Numéro: 1
Année: 2019
Première Page: 97
Dernière Page: 120

Are Election Results More Unpredictable? A Forecasting Test
Journal: Political Science Research and Methods
Richard Nadeau
Ruth Dassonneville
Michael S. Lewis-Beck

La prédiction électorale : défense et réflexion épistémologique
Journal: Argument
Volume: 21
Numéro: 1
Année: 2018
Première Page: 143
Dernière Page: 155

10 Downing Street: Who's Next? Seemingly Unrelated Regressions to Forecast UK Election Results
Journal: Journal of Elections, Public Opinion and Parties

Forecasting Dutch elections: An initial model from the March 2017 legislative contests
Journal: Research and Politics
Volume: 4
Numéro: 3
Année: 2017
Première Page: 1
Dernière Page: 7
Ruth Dassonneville
Michael S. Lewis-Beck

Playing the Synthesizer with Canadian Data: Adding Polls to a Structural Forecasting Model
Journal: International Journal of Forecasting
Volume: 37
Numéro: 1
Année: 2021
Première Page: 289
Dernière Page: 301
Richard Nadeau
Bruno Jérôme

State-Level Forecasts for the 2020 U.S. Presidential Election: Tough Victory Ahead for Biden
Journal: PS: Political Science and Politics
Volume: 54
Numéro: 1
Année: 2021
Première Page: 77
Dernière Page: 80
Bruno Jérôme
Véronique Jérôme
Richard Nadeau

Did You See It Coming? Explaining the Accuracy of Voter Expectations for District and (Sub)national Elections in Multi-Party Systems
Journal: Electoral Studies
Volume: 71
Année: 2021

A Technocratic View of Election Forecasting: Weighting Citizens’ Forecasts According to Competence
Journal: International Journal of Public Opinion Research
Année: 2021