Original title: The 2020 Election In The United States: Beta Regression Versus Regression Quantiles
Authors: Kalina, Jan
Document type: Papers
Conference/Event: RELIK 2021: Reproduction of Human Capital - mutual links and connections, Praha (CZ), 20211104
Year: 2021
Language: eng
Abstract: The results of the presidential election in the United States in 2020 desire a detailed statistical analysis by advanced statistical tools, as they were much different from the majority of available prognoses as well as from the presented opinion polls. We perform regression modeling for explaining the election results by means of three demographic predictors for individual 50 states: weekly attendance at religious services, percentage of Afroamerican population, and population density. We compare the performance of beta regression with linear regression, while beta regression performs only slightly better in terms of predicting the response. Because the United States population is very heterogeneous and the regression models are heteroscedastic, we focus on regression quantiles in the linear regression model. Particularly, we develop an original quintile regression map, such graphical visualization allows to perform an interesting interpretation of the effect of the demographic predictors on the election outcome on the level of individual states.
Keywords: elections results; electoral demography; heteroscedasticity; outliers; quantile regression
Host item entry: RELIK 2021. Conference Proceedings, ISBN 978-80-245-2429-0

Institution: Institute of Computer Science AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: https://relik.vse.cz/2021/download/pdf/380-Kalina-Jan-paper.pdf
Original record: http://hdl.handle.net/11104/0328134

Permalink: http://www.nusl.cz/ntk/nusl-508468


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