Forecasting two-horse races in new democracies: Accuracy, precision and error

The purpose of this article is to explore electoral forecasting in two-horse races in new democracies. Specifically, it applies a Bayesian dynamic linear model (coined the Two-Stage Model, TSM) to look at the 2020 Chilean two-question national plebiscite. The ultimate objective is to test the TSM in...

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Main Author: Kenneth Bunker
Format: Article
Language:English
Published: Ediciones Universidad de Salamanca 2022-06-01
Series:Revista Latinoamericana de Opinión Pública
Subjects:
Online Access:https://revistas.usal.es/index.php/1852-9003/article/view/25374
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author Kenneth Bunker
author_facet Kenneth Bunker
author_sort Kenneth Bunker
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description The purpose of this article is to explore electoral forecasting in two-horse races in new democracies. Specifically, it applies a Bayesian dynamic linear model (coined the Two-Stage Model, TSM) to look at the 2020 Chilean two-question national plebiscite. The ultimate objective is to test the TSM in terms of accuracy (how close the forecast is to the election results), precision (how close the forecast is to other methods of prediction) and error (how the forecast deviates from perfect accuracy/precision). The article finds that while the TSM does appear to be a stable estimator, its accuracy and precision is affected under certain conditions. Using the difference in the results for each of the two questions, the article discusses how sharp and unexpected shifts in electoral preferences can affect forecasts.
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spelling doaj.art-1c28ce3561c94ebeb5dac383772930c32022-12-22T00:20:06ZengEdiciones Universidad de SalamancaRevista Latinoamericana de Opinión Pública1852-90032660-700X2022-06-0111110.14201/rlop.2537422519Forecasting two-horse races in new democracies: Accuracy, precision and errorKenneth Bunker0https://orcid.org/0000-0002-4579-6132Universidad Diego PortalesThe purpose of this article is to explore electoral forecasting in two-horse races in new democracies. Specifically, it applies a Bayesian dynamic linear model (coined the Two-Stage Model, TSM) to look at the 2020 Chilean two-question national plebiscite. The ultimate objective is to test the TSM in terms of accuracy (how close the forecast is to the election results), precision (how close the forecast is to other methods of prediction) and error (how the forecast deviates from perfect accuracy/precision). The article finds that while the TSM does appear to be a stable estimator, its accuracy and precision is affected under certain conditions. Using the difference in the results for each of the two questions, the article discusses how sharp and unexpected shifts in electoral preferences can affect forecasts.https://revistas.usal.es/index.php/1852-9003/article/view/25374bayesian inference; election campaigns; new democracies; public opinion; plebiscites
spellingShingle Kenneth Bunker
Forecasting two-horse races in new democracies: Accuracy, precision and error
Revista Latinoamericana de Opinión Pública
bayesian inference; election campaigns; new democracies; public opinion; plebiscites
title Forecasting two-horse races in new democracies: Accuracy, precision and error
title_full Forecasting two-horse races in new democracies: Accuracy, precision and error
title_fullStr Forecasting two-horse races in new democracies: Accuracy, precision and error
title_full_unstemmed Forecasting two-horse races in new democracies: Accuracy, precision and error
title_short Forecasting two-horse races in new democracies: Accuracy, precision and error
title_sort forecasting two horse races in new democracies accuracy precision and error
topic bayesian inference; election campaigns; new democracies; public opinion; plebiscites
url https://revistas.usal.es/index.php/1852-9003/article/view/25374
work_keys_str_mv AT kennethbunker forecastingtwohorseracesinnewdemocraciesaccuracyprecisionanderror