Abstract
When the number of observed elections is low, subnational data can be used to perform electoral forecasts. Turgeon and Rennó (2012) applied this solution and proposed three forecasting models to analyze Brazilian presidential elections (1994-2006). The models, adapted from forecasting models of American and French presidential elections, considers economic and political factors. We extend their analysis to the recent presidential elections in Brazil (2010, 2014 and 2018) and find that the addition of the three recent elections does not improve the accuracy of our forecast models although it strengthens the relationship between the explanatory variables and vote for the incumbent. We also find that models based on the popularity of the incumbent outperform those based on trial-heat polls and that electoral forecast models can survive earthquake elections like the 2018 election that led to the unexpected rise of “outsider” and extremist candidate Jair Bolsonaro.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
